Python Developer in India

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Workforce Identity Cloud Okta Workforce Identity Cloud (WIC) provides easy, secure access for your workforce so you can focus on other strategic priorities, such as reducing costs and doing more for your customers. If you like to be challenged and have a passion for solving large-scale automation, testing, and tuning problems, we would love to hear from you. The ideal candidate is someone who exemplifies the ethics of, “If you have to do something more than once, automate it” and who can rapidly self-educate on new concepts and tools. Position Overview: The Staff Site Reliability Engineer (SRE) will play a key role in building and managing Kubernetes platforms that support cloud-native applications and services. This position focuses on architecting and managing reliable, scalable, and secure Kubernetes-based platforms on AWS, ensuring high availability and performance while optimising costs and automation. The ideal candidate will have hands-on experience with AWS infrastructure, Kubernetes platform creation, Helm charts, Karpenter scaling, and Istio service mesh. Key Responsibilities: Kubernetes Platform Creation: Design, implement, and maintain highly available, scalable, and fault-tolerant Kubernetes platforms. Ensure clusters are optimised for production workloads, providing high resilience and operational efficiency. AWS Infrastructure Management: Build, manage, and optimise AWS cloud infrastructure, including EKS, ECS, S3, VPCS, RDS, IAM, and more. I

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Workforce Identity Cloud Okta Workforce Identity Cloud (WIC) provides easy, secure access for your workforce so you can focus on other strategic priorities, such as reducing costs and doing more for your customers. If you like to be challenged and have a passion for solving large-scale automation, global traffic routing, and resilient cloud infrastructure problems, we would love to hear from you. The ideal candidate is someone who exemplifies the ethics of, “If you have to do something more than once, automate it” and who can rapidly self-educate on new network topologies, multi-cloud ecosystems, and agentic engineering models. Position Overview: The Staff Software Engineer - Infrastructure will play a foundational role in architecting, evolving, and securing Okta's global core network fabric and multi-cloud platform layers. This position focuses on building highly resilient, edge management in AWS and GCP cloud, executing enterprise-wide cloud migrations (AWS to GCP), enforcing absolute Zero-Trust primitives (mTLS / TLS 1.3), and integrating cutting-edge AI automation layers (Agentic SRE) into our day-to-day operations. As a Staff Engineer on this team, you will act as a key technical anchor in India, working closely with global counterparts to maintain Okta's high-availability SLAs while protecting the platform against active global DDoS attacks. Key Responsibilities: Global Ingress & Routerless Evolution (CFSaaS): Design and engineer Next-Gen traffic

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through a combination of strategic partnerships and self-built campuses, we are scaling the compute, storage, and networking platforms that power frontier AI training and inference. The Scaling Analytics team builds the data and software systems that help Industrial Compute understand, plan, and operate infrastructure at global scale. We work across capacity, hardware, storage, infrastructure software, and operational systems to connect fragmented sources of infrastructure data and make that information reliable and usable for engineering and planning. As OpenAI's infrastructure footprint grows, CPU and storage data increasingly spans internal platforms, vendor systems, APIs, databases, object storage, capacity management systems, and operational tooling. Building reliable connections across these environments is critical to understanding available capacity, utilization, fleet state, and infrastructure growth. About the Role We are seeking a Data Engineer to build the data systems and integrations that connect OpenAI's CPU, storage, and supporting infrastructure platforms. This role sits at the intersection of data engineering and backend software engineering. Rather than focusing primarily on traditional analytical pipelines, you will build the software and integrations required to collect, normalize, and make infrastructure data available across a heterogeneous set of systems. CPU and storage data may originate from internal infrastructure platforms, vendor APIs, databases, object storage, capacity systems, and operational services. You will determine how to reliably connect these systems and where those integrations should live—whether within an existing infrastructure service, an orchestration framework, a scheduled workload, or a purpose-built application. You will work closely with Infrastructure Engineering, Capacity Engineering, Storage,

About the Role As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In this role, you will: Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role This is an opportunity to serve as a key partner and advisor on Notion's Business Operations team, working primarily with our Engineering, Product, and Design teams. Business Operations is a cross-functional team that partners with senior leaders across the company, focusing on high-impact strategic projects and analysis. In this role, you'll independently identify the highest-leverage opportunities, define the problem, drive execution, and keep going. If you thrive when given full ownership and a blank page, this role is for you. You'll work hand-in-hand with senior leadership to identify, structure, and act on the most challenging strategic and operational questions impacting our business. And you’ll use AI to build scalable systems and processes that multiply your impact. What You'll Achieve Proactively surface and prioritize high-impact strategic and operational opportunities and own them end-to-end from scoping through execution Work cross-functionally with product, engineering, and go-to-market leaders to define and implement strategy across all Notion products, driving increased value for our users, our customer

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: You're joining Notion's People Analytics & Operations team as part of an 18-month rotational program -- the group that builds the insights engine powering every people decision Notion makes. We look for slope over intercept. We care less about where you trained and more about what you've built. If you've ever rebuilt a broken process because it was bothering you, used AI to do something you couldn't have done alone, or found yourself reading about labor economics for fun -- you're the person we're looking for. Over 18 months, you'll rotate across people operations, people analytics, and compensation/benefits. Every rotation is real work with real ownership. On the analytics side, you'll build dashboards that land in exec review, write SQL that powers headcount models, and prototype AI-assisted workflows that help our team move faster. On the operations side, you'll run the HR engine -- managing employee lifecycle transactions in Workday, owning onboarding and offboarding coordination end-to-end, triaging and resolving employee requests, and keeping our people data clean and audit-ready. You'll be paired with a sen

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Platform Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning/sharding strat

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who we are Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the AI employee. We are founded by ex-Google, Coinbase, Okta executives and serial entrepreneurs. We’ve raised capital from notable investors such as Accel Partners, Naspers, Section32 and a host of prominent Silicon Valley Angels including Sheryl Sandberg (Facebook/Google), Divesh Makan (Iconiq Capital), Jerry Yang (Yahoo), Dustin Moskovitz (Facebook/Asana), David Baszucki (Roblox CEO) and Gokul Rajaram (Doordash, Square, Google). Our team is a powerhouse of talent, comprising engineers from leading tech companies like Google, Microsoft Research, Facebook, Square/Block, and Coinbase. All our team members hail from top-tier educational institutions such as Stanford, MIT, UC Berkeley, CMU and Indian Institute of Technology. We’re well funded by the top investors and angels in the world. Ema is based in Silicon Valley and Bangalore, India. This will be a hybrid role where we expect employees to work from office three days a week. Who you are We are seeking an

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who is accustomed to solving customer’s most complex problems and closing large deals. In this role you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. As a Snowflake Solution Engineer you must share our passion about reinventing the database space, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences. Location: Must be based in Atlanta, Tennessee, Florida, North Carolina OR South Carolina IN THIS ROLE YOU WILL GET TO: Present Snowflake technology and vision to executives and technical contributors at prospects and customers Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and compleme

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for world-class Solution Engineers to join our Global field teams whose technical skills and customer savvy will help customers understand and utilise the value of the cutting-edge data platform that we are building. They must share our passion about reinventing the data platform and thrive in a dynamic environment. The Solution Engineer will work hand-in-hand with Sales, Product, Engineering, and Marketing. In this role you will work directly with the account sales team on a handful of global accounts with GCCs in India to accelerate their Snowflake journey. The Solution Engineer will be responsible for providing the technical expertise to make Snowflake customers successful in driving existing projects and uncover new use cases. This data architect will have a broad range of skills and experience ranging from data architecture to ETL/ELT, data science, security, performance analysis, analytics, etc. He/she will have the insight to make the connection between a customer’s specific business problems and Snowflake’s solution, the customer-facing skills to communicate that connection and vision to a wide variety of technical and executive audiences, and the technical skills to be able to not only build demos and execute proof-of-concepts but also to provide con

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer, Snowflake Natsec Running Snowflake in public sectors in different countries and regions, even in different industry verticals, requires us to build a compliant, secure, and auditable infrastructure. Many key design decisions are deeply rooted in the Snowflake product architecture. As a Senior Software Engineer, you will be responsible for leading several key areas and collaborating with various engineering groups in addition to the Public Sector team. To be successful in the area, you will need to have (and continue to build) a broad and in-depth knowledge base on cloud infrastructure, privacy, and governance, compliance controls, data security and data residency in various aspects of Snowflake. AS A SENIOR SOFTWARE ENGINEER AT SNOWFLAKE YOU WILL: Solve real business needs at large scale by applying your software engineering and analytical problem solving skills. Design, implement and maintain scalable distributed systems for our cloud automation platform that include cloud control plane, Kubernetes container platform and traffic and networking. Work directly with customers to quickly understand their critical problems and design and implement solutions Deploy and maintain availability of cloud compute servers and Kubernetes cluster that power the

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Role As a Senior Solution Engineer at Snowflake, you are the technical trusted advisor to our customers and prospects. You bridge the gap between complex technical capabilities and business outcomes, equally comfortable whiteboarding architecture with a data engineering team and presenting ROI to a CFO. You own the technical win. Responsibilities Lead technical discovery, solution design, and proof-of-value engagements with enterprise customers across all industries Translate complex business requirements into architectures leveraging the Snowflake Data Cloud (data engineering, data science/AI/ML, data sharing, applications, and security/governance) Deliver compelling technical presentations, demos, and workshops to audiences ranging from individual contributors to C-suite executives Partner with Account Executives to drive pipeline, accelerate deals, and close business Serve as the voice of the customer back to Product and Engineering teams Build and maintain reusable assets: demo environments, reference architectures, and solution accelerators Stay current on competitive landscape, industry trends, and emerging capabilities across the data & AI ecosystem Required Qualifications 8+ years of experience spanning multiple disciplines: data engineering, analytics