Lead Software Engineer - Cloud/Python/AI Engineer

Lead Software EngineerWe have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.As a Lead Software Engineer at JPMorganChase within the Corporate Sector - Data Visualization & BI team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.This role requires a strong AI-forward mindset. We are looking for engineers who don't just use AI — they think with it, build with it, and know when not to use it.Job ResponsibilitiesLeverage AI-powered coding assistants (e.g., GitHub Copilot, Claude) as core tools in daily development workflows — writing, reviewing, debugging, and refactoring code with speed and precisionValidate, critique, and iterate on AI-generated outputs rather than accepting them uncritically; apply sound engineering judgment to AI suggestionsContinuously evaluate emerging AI tools and techniques, driving adoption where they deliver measurable productivity and quality gainsDesign, build, and deploy enterprise-grade AI solutions including Retrieval-Augmented Generation (RAG) pipelines, agentic AI systems, and LLM-powered workflowsArchitect AI systems with production-level concerns: scalability, cost management, latency, data privacy, hallucination mitigation, and observabilityDesign, build, and deploy agentic solutions with enterprise grade identity, guardrails, tracing etc.Execute creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches. Develop secure, high-quality production code and review and debug code written by othersApply strong systems thinking — understand how components connect end-to-end, where failures occur, and how changes propagate across distributed systemsIdentify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stabilityLead evaluation sessions with external vendors, startups, and internal teams to probe architectural designs, technical credentials, and applicability within existing systemsInfluence stakeholders and drive alignment across teams without direct authorityOwn outcomes end-to-end — take accountability when things go well and when they don'tRequired Qualifications, Capabilities, and SkillsFormal training or certification in software engineering concepts and 5+ years of applied experienceDemonstrated fluency with AI-assisted development tools (e.g., GitHub Copilot, Claude Code, Cursor) — not just familiarity, but daily integrated useHands-on experience building AI/ML-powered features or products — RAG systems, AI agents, prompt engineering, or LLM integration in production or near-production environments3+ years of hands-on experience with AWS cloud servicesProficiency in Python programmingExperience with Django or another web backend frameworkExperience with React or another modern UI frameworkStrong experience with Terraform and infrastructure-as-code principlesSolid understanding of system design, data structures, and algorithmsDemonstrated adaptability — ability to operate effectively in fast-changing, ambiguous environments and deliver at speedStrong problem-solving skills with a structured, evidence-based approach to decision-makingPreferred Qualifications, Capabilities, and SkillsExperience with AI orchestration frameworks (LangChain, LlamaIndex, CrewAI, Google ADK, or similar)Experience with vector databases (Pinecone, Weaviate, pgvector, Chroma, or similar) and embedding modelsUnderstanding of LLM evaluation, guardrails, and responsible AI practices (accuracy, cost, bias, data privacy)Exposure to Data Engineering tools and platforms, especially DatabricksFamiliarity with CI/CD pipelines and DevOps practicesKnowledge of other cloud platforms (Azure, GCP) is a plus