Deployment Strategist Lead Jobs

Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a degree in Computer Science o

Roles and Responsibilities Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a d

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Site Reliability Engineering at Affirm is a small, yet crucial, team that helps our Engineering partners to “Operate What They Own” with excellence to protect their customers’ experience. SRE accomplishes this through defining frameworks and best practices for operating applications, building tooling, and providing training and consulting. Some of the many SRE responsibilities are: Providing data and visibility to teams and leadership on application performance Guiding the development of SLOs Driving the Incident Management and Analysis process Steering the implementation of Change Management and Deployment practices Engaging in service and architectural conversations Recommending observability and alerting configurations The SRE team benefits from experience across many domains including: infrastructure, platform, and distributed systems capacity management, load and chaos testing automation, observability, and configuration management development and product experience The SRE team is seeking motivated software and systems engineers with the experience to build, iterate on, and expand incident lifecycle, reliability, and resilience practices throughout Affirms Engineering organization and beyond. What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with infrastructure, product management, developer experience & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify technical solutions

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

Role: Senior AI Engineer Location: Hyderabad, India (Hybrid) Department: Product Development About the Role GHX is building a cutting-edge LLM-powered document understanding platform focused on classification, structured data extraction, and intelligent orchestration at scale. This is a high-impact AI engineering role where you will own the full lifecycle—from problem framing to production deployment . Initially, you will focus on prompt engineering and evaluation systems , building the quality foundation for AI performance. Over time, the role expands into agent orchestration, system architecture, and migration of rule-based systems to LLM-driven pipelines . A strong foundation in software engineering (5+ years) is essential. This role demands engineering rigor across both traditional system design and AI system behavior . Core Responsibilities 1. Prompt Engineering Design prompts for diverse document classification and extraction tasks Treat prompts as formal specifications (precise, structured, and edge-case-aware) Develop few-shot, chain-of-thought, and structured output templates Manage prompt lifecycle: versioning, testing, and rollback 2. LLM Output Evaluation Create and maintain ground truth datasets Build automated evaluation pipelines (precision, recall, field-level accuracy) Identify and resolve conceptually incorrect outputs despite surface correctness 3. AI Agent Orchestration Design multi-agent workflows for document processing Implement tool-use patterns and integrate MCP servers Optimize orchestration for scale and efficiency 4. Software Engineering Develop production-grade APIs and backend services Apply Clean Architecture / DDD principles Write maintainable, testable Python code Contribute to CI/CD, deployment, and observability systems 5. Stakeholder Collaboration Act as a bridge between business stakeholders and AI systems Translate product requirements into technical architectures Communicate system behavior, limitations, and quality

Description: Graviton Research Capital LLP, Gurgaon is looking to hire Software Engineers for our Core Technology team which has some of the best programmers in India working on cutting edge technologies to build a super fast and robust trading infrastructure handling millions of dollars worth of trading transactions every day. As a Senior Software Engineer with Graviton your responsibilities will include: Designing and implementing a high-frequency automated trading system, that trades on multiple exchanges Building live reporting and administration tools for the trading system Performance optimization and improving the overall latency of systems, through algorithm research and using cutting edge tools and techniques End-to-end ownership of modules, including designing, development, deployment and support Growing the team through involvement in the regular hiring process and occasional campus recruitments Requirements : The ideal requirements for our candidates are: A degree in Computer Science 3-5 yrs Experience with C/C++ and object-oriented programming Experience in HFT industry Expertise in algorithms and data structures Excellent problem solving skills Strong communication skills A working knowledge of Linux systems Any of the following is a plus: A good understanding of TCP/IP and Ethernet Knowledge of any other programming language e.g. Java, Scala, Python, bash, Lisp, etc. Familiarity with parallel programming models and parallel algorithms Experience with big data environments e.g. Hadoop, Spark etc. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation Annual international team outing Fully covered commuti

Role Overview You’re a hands-on backend engineer who enjoys owning features end to end and working on real products that customers rely on every day. In this Software Engineer II role, you’ll help build and evolve a Third Party Risk Management SaaS platform using Laravel and PHP, designing scalable APIs and services that keep performance and reliability front and center. You’ll work in a product-focused team that owns its services from architecture and implementation through deployment, monitoring, and continuous improvement. You’ll mentor junior engineers, influence technical decisions, and use modern AI-powered tools thoughtfully to ship better code faster. If you’re looking for a mid-level role with real ownership, modern tooling, and the chance to grow your impact, this is for you. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design, build, and maintain backend features and RESTful APIs in Laravel within a modern TALL stack environment. Own well-defined stories from implementation through deployment, monitoring, and iteration, ensuring performance and reliability. Contribute to architectural discussions and technical decisions that shape the Third Party Risk Management platform. Review code, improve test coverage, and strengthen CI/CD and engineering standards across the team. Mentor Software Engineer I colleagues through code reviews, pairing, and knowledge sharing. Use AI tools (e.g. GitHub Copilot, ChatGPT) to accelerate coding, debugging, testing, and documentation—while critically validating outputs and ensuring safe, responsible use. These are the essentials you’ll need to get an interview 3–5 years of professional software engineering experience in an agile, fast-paced environment. Strong experience with PHP and Laravel, ideally within the TALL stack (Tailwind, Alpine.js, Laravel, Livewire). Solid understanding of relational databases (MySQL or MariaDB), including data modelling and query optimisation. Experience designin

Role Overview Build reliable software services that power products, platforms, and business decisions. As a Senior Software Developer, you’ll design and deliver scalable applications, backend services, and integrations that perform well in production and evolve with changing business needs. You’ll apply strong software engineering practices across APIs, data-intensive applications, cloud services, AI-enabled solutions, and deployment pipelines. You’ll help shape technical solutions, improve system reliability, and contribute to a high-quality engineering culture. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design and develop scalable backend services and applications using Python or TypeScript. Lead the development of APIs, integrations, reusable software components, and AI-enabled features. Build reliable solutions for data ingestion, manipulation, service-to-service communication, and intelligent automation. Apply AI technologies and modern software engineering practices to improve product capabilities, developer productivity, and operational efficiency. Make sound technical decisions around architecture, performance, security, scalability, and maintainability. Deploy and operate applications using AWS services and CI/CD practices while improving testing, monitoring, documentation, and delivery standards. These are the essentials you’ll need to get an interview 5+ years of professional experience developing and delivering production software. Strong hands-on experience with Python; TypeScript or similar languages is also valuable. Proven experience building backend services, APIs, integrations, and service-oriented applications. Experience applying AI technologies, such as generative AI, machine learning services, intelligent automation, or AI-enabled application features. Strong understanding of software design principles, testing, debugging, performance optimization, and secure development. Experience working with cloud platfor

Here's a summary of the role: Do you love building scalable cloud platforms and solving complex engineering problems with modern technologies? As a Senior Software Engineer at Diligent, you'll design and deliver high-performing , serverless applications that power our global SaaS platform. You'll work extensively with TypeScript, Node.js, AWS, and event-driven microservices, owning services from design to deployment and production monitoring. This is an opportunity to influence technical decisions, mentor engineers, and explore how AI can transform software development and engineering productivity. If you're passionate about cloud-native architectures, distributed systems, and building software that scales to millions of users, we'd love to meet you. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design and build scalable backend services and event-driven microservices using TypeScript and AWS. Develop secure APIs and integrations that power reporting, analytics, and dashboard experiences. Build and maintain serverless solutions using AWS services such as Lambda, EventBridge , SQS, and DynamoDB. Drive engineering excellence through testing, observability, automation, and production readiness practices. Contribute to infrastructure-as-code and CI/CD pipelines using AWS CDK and modern DevOps practices. Mentor engineers, participate in architecture discussions, and champion the use of AI tools to improve development efficiency. These are the essentials you'll need to get an interview: 6-8 years of professional software engineering experience. Strong experience with TypeScript, Node.js, and modern backend development patterns. Hands-on experience building cloud-native applications on AWS. Strong understanding of serverless architectures and event-driven microserv

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,