Lead Python Specialist Jobs

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 hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

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 hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

About the role Chime is looking for a Director of Engineering to lead our AI & App Experience (AAX) organization — the team building the next generation of the Chime member experience. AAX owns Jade, Chime’s AI-powered financial assistant, our AI platform infrastructure as well as the core app experiences and shared design system. In this role, you’ll own the multi-quarter strategy for AAX engineering, translating company priorities into scalable plans across these teams. You’ll build and lead a bench of TLM (tech leader managers) and senior technical staff, set the technical bar for how Chime builds AI-native, member-facing products, and partner with Product, Design, Data Science, and our Risk team to shape where AAX invests next. This is a role for a leader who is equally comfortable setting long-range technical vision and staying close enough to the details to guide hard architectural calls — someone who has helped build or scale AI/LLM-powered consumer products and knows how to grow the engineering leaders around them. In this role, you can expect to In partnership with our product team you will own the multi-quarter strategy for AAX engineering, translating company and product priorities into our roadmap plans across consumer facing AI experiences, AI Platform, App Journey, and Design Systems. Build, lead, and hire a high-caliber leadership bench of highly technical leaders/IC’s as well as building a team culture that exemplifies a builder mindset. Partners with your team to set technical direction for the org, driving architectural alignment across our consumer facing AI experiences, AI Platform, App Journey, and Design System. You will continue to drive our AI-native engineering culture: setting the bar for how LLM-powered features get shipped safely at scale. Own engineering’s strategic role in product direction, partnering with Product, Design, Data Science, and Risk leadership to shape roadmaps, challenge assumptions, and integr

About the Role: We are seeking an experienced Risk Management professional to lead and strengthen the organisation's Operational Risk and Outsourcing Risk Management framework. The role will be responsible for identifying, assessing, monitoring, and mitigating operational and third-party risks across payment products, merchant acquiring, cross-border payments, and outsourced business operations. The incumbent will work closely with business, operations, compliance, technology, audit, and leadership teams to ensure adherence to regulatory requirements, network guidelines, and internal risk policies. Key Responsibilities Operational Risk Management: Develop, implement, and enhance the Operational Risk Management (ORM) framework, including Risk and Control Self-Assessments (RCSAs), across the organisation. Identify, assess, monitor, and mitigate operational risks arising from payment operations, merchant onboarding, transaction processing, and customer servicing. Drive corrective action plans arising from RCSA findings and control gaps. Monitor Key Risk Indicators (KRIs), operational losses, incidents, and control effectiveness. Lead root cause analysis and remediation for operational risk events. Own SOP and policy lifecycle management — including drafting, versioning, and periodic review — for all operational risk policies and procedures. Outsourcing Risk Management: Manage end-to-end outsourcing risk governance for third-party vendors involved in KYC verification, PAN validation, customer onboarding, payment processing, and other critical functions. Maintain and operate a vendor categorisation framework (IT/Non-IT, critical/non-critical outsourcing) and ensure risk assessments are calibrated to vendor tier and exposure. Ensure compliance with RBI Outsourcing Guidelines, PA Master Directions 2025, and all applicable regulatory requirements. Conduct vendor due diligence, risk assessments, performance reviews, and periodic audits. Monitor SLA adherence, control ef

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. . About the Role, Mission or Department Overview As an Engineering Manager for Cybersecurity at The New York Times, you will lead the team responsible for building and operating the platforms, tooling and services that keep our systems secure at scale. Our engineers design and run the infrastructure that underpins vulnerability scanning, secrets management, secure-by-default platforms and other core security capabilities used across the entire technology organization. You will work with partners in Cybersecurity, Developer Platforms, Enterprise Technology and Product Engineering to deliver reliable, developer-friendly security services. This is a hands-on leadership role where you'll balance people management with technical decision-making. You'll coach engineers, shape technical roadmaps, and help your teams make risk-informed decisions that support both engineering goals and the broader business. You will report to the Director of Engineering, Cybersecurity within the Information Security organization. Information Security helps prevent The Times from becoming news. Our department protects the journalists who report the news, the colleagues who support them, the platforms they rely on every day and the readers who depend on our products. We run programs across security engineering, application security, incident response, governance and more, partnering closely with teams throughout the company to keep our systems dependable and safe. Resp

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. You will work remotely from Germany and will be reporting to Sr. Director, Engineering You Will: Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer's workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn't done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to so

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge , we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability. Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data. Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently. Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets. Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions. Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts. Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments. Partner closely with engineering managers, product leaders, and researchers to scope high-impac

We are hiring Senior / Lead Engineers to design, build, and scale robust, production-grade data and platform systems for a product portfolio within Blenheim. This is a hands-on engineering role where you will own complex problem areas end-to-end, influence system architecture, mentor engineers, and deliver scalable solutions in a fast-growing, product-led environment. If you enjoy working with ambiguity, building platforms from the ground up, and shipping real business impact, we’d love to hear from you. About Blenheim Chalcot: Blenheim Chalcot India is part of Blenheim Chalcot, a global venture builder headquartered in London. With over 26 years of innovation, we've been at the forefront of creating some of the most groundbreaking GenAI-enabled companies. Our ventures lead the charge in digital disruption across a spectrum of industries, from FinTech to EdTech, GovTech to Media, and beyond. Our global presence spans the US, Europe, and Southeast Asia, with a portfolio that employs over 3,000 individuals, manages assets exceeding £1.8 billion, and boasts total portfolio sales of over £500 million. The Role: As a Senior / Lead Engineer, you will play a key role in designing and delivering scalable systems across core platforms. You will collaborate closely with Product, Data, and Engineering teams in Mumbai and London, helping shape technical direction while remaining hands-on. Key Responsibilities: Successful candidates will take a leading role within our Engineering Centre of Excellence in Mumbai, with day to day responsibilities which will include. Lead and mentor a team of engineers, fostering a culture of collaboration and continuous improvement. Oversee the planning and execution of projects, ensuring alignment with business objectives and timelines. Provide technical guidance and expertise to the team, promoting best practices in engineering. Collaborate with cross-functional teams to understand requirements and deliver effect

The role Scale builds enterprise AI systems deployed into production. As a Solutions Architect, you lead technical execution for enterprise deals in your vertical from initial discovery through deal close, and remain involved post-sale to support account growth. You own an assigned set of enterprise accounts. You conduct technical discovery, evaluate technical feasibility, build solution prototypes, and serve as the main technical point of contact for customer engineering and leadership teams. You work alongside three primary partners: the Account Executive (commercial owner), the Project Manager (delivery owner), and the Tech Lead (engineering lead for implementation). What you will own Technical discovery and qualification. Lead technical discovery and complete the Technical Qualification Checklist, evaluating feasibility, data readiness, integration requirements, security/compliance, evaluation readiness, and stakeholder alignment. Provide clear go/no-go recommendations for prospective deals. Evaluation and success criteria. Define performance metrics and evaluation criteria before proposal stage, including quality dimensions, baselines, evaluation datasets, and subject-matter expert access requirements. Customer workshops. Lead executive technical workshops for target use cases. Prepare pre-read materials and build working prototypes or live demos to validate proposed technical architectures. Statement of Work (SOW) input. Supply the technical input package for SOW creation (architectural approach, prototype findings, risks, dependencies, and assumptions) and review draft SOWs for technical accuracy. Post-sale account engagement. Maintain long-term technical engagement with signed accounts, identify expansion opportunities for new use cases, and share delivery feedback with GTM teams. Vertical technical assets. Develop reference architectures, demo environments, discovery templates, and evaluation frameworks for your assigned industry vertical. Wha