AI Automation Engineer Associate
JPMorgan Chase5 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design and operate production-grade AI assistants combining language models, multimodal models, business rules, retrieval, and tool integrations.
- Engineer graph-based, multi-stage workflows covering ingestion, model execution, tool invocation, validation, and post-processing.
- Implement structured outputs, prompts, retrieval-augmented generation, agentic patterns, document digitization, OCR, validation, and exception handling.
- Define success metrics and improve solution quality through golden datasets, regression tests, error analysis, production monitoring, and measurable remediation.
- Write secure, maintainable, well-tested production code and reusable components, including integrations with external tools and services.
- Troubleshoot model, retrieval, tool-integration, and post-processing issues and drive root-cause analysis and preventative fixes.
- Embed Responsible AI controls, guardrails, governance, auditability, and traceability into delivery and operations.
- Produce recurring health reporting covering adoption, accuracy, override rates, exception rates, latency, drift, and cost.
- Facilitate workshops, process walkthroughs, and shadowing with operations users to translate needs into requirements, controls, and acceptance criteria.
Requirements
- At least 5 years of hands-on experience in applied AI, machine learning, or AI-powered automation delivering production or production-like solutions.
- Strong Python proficiency, including asynchronous programming, for clean, maintainable, and well-tested code.
- Experience with LLM techniques including prompt engineering, structured or JSON-schema outputs, and robustness methods.
- Experience using LangGraph or an equivalent graph-based orchestration framework for multi-step AI workflows.
- Experience defining and validating schemas with Pydantic and processing data with pandas.
- Experience implementing OCR and document digitization workflows, including PDF extraction, AWS Textract or equivalent tools, cleanup, validation, and exception handling.
- Experience integrating external tools and services through APIs, including tool-using assistant patterns with validation and error handling.
- Knowledge of automated testing, continuous integration and delivery, secure development, logging, metrics, tracing, runbooks, production readiness, and incident response participation.
- Experience using Git and a hosted repository platform for branching, pull requests, and code review.
- Ability to define objective success metrics, evaluate solution quality, communicate with technical and non-technical stakeholders, and perform structured root-cause analysis.
- Preferred experience with AI-powered analytics, workflow automation, intelligent process tools, enterprise LLM or agentic applications, service health, SLOs, RAG, embeddings, vector stores, retrieval evaluation, grounding, and hallucination mitigation.
- Preferred knowledge of confusion matrices, precision, recall, F1, error analysis, A/B testing, and statistical significance.
- Preferred experience with PyTorch, TensorFlow, or scikit-learn and scalable, observable backend or API deployment using containerization and cloud-native technologies.
- A Master’s degree specializing in AI, machine learning, or a related quantitative field is preferred.
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About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.