Senior Lead Software Engineer- Python AI

About the job

Responsibilities

• Enhance products with AI-driven features to improve user experience, efficiency, and resilience.
• Design, build, and deploy production-grade AI applications, including LLM workflows, RAG, and agentic systems.
• Build agentic workflows with enterprise controls for identity, authorization, guardrails, tracing, evaluation, and auditability.
• Develop automation solutions to reduce manual effort and eliminate operational issues, incorporating self-healing and intelligent triage.
• Architect AI systems considering production concerns such as latency, scalability, cost, model selection, observability, reliability, and failure modes.
• Establish and apply AI engineering standards for prompting, RAG design, evaluation, logging, and release readiness.
• Drive AI architecture reviews and contribute to reference architectures for model hosting, orchestration, data access, and tool execution.
• Identify and mitigate risks across the AI lifecycle, including data privacy, security, bias, model misuse, prompt injection, and third-party risk.
• Partner with product, design, risk, legal/compliance, and engineering stakeholders to align on outcomes and success metrics.
• Lead technical evaluations of vendors and platform providers, assessing capabilities, integration, security, and total cost of ownership.
• Research emerging AI capabilities and translate findings into practical guidance, prototypes, and adoption recommendations.
• Educate and enable teams through documentation, workshops, design reviews, and coaching to improve AI fluency and delivery consistency.
• Execute creative software solutions, technical troubleshooting, and hands-on development, writing and reviewing secure, high-quality production code.
• Influence stakeholders and drive alignment across teams without direct authority, owning outcomes end-to-end.

Requirements

• 5+ years of applied engineering experience with formal training or certification in software engineering concepts.
• Hands-on experience delivering AI-powered features in production or near-production environments (LLMs, RAG, agents, workflow automation, or decision support systems).
• Strong proficiency in Python, with the ability to build maintainable services, libraries, and pipelines.
• Experience building APIs and services using Django, FastAPI, or similar frameworks.
• Experience building modern UIs using React or similar frameworks, or ability to partner closely with frontend teams.
• Strong system design skills emphasizing secure distributed systems, reliability, and operational excellence.
• Practical understanding of Responsible AI/model risk concepts (evaluation, guardrails, privacy, bias, explainability, safe deployment).
• Experience implementing observability (logging, metrics, tracing) and AI-specific monitoring (quality, drift, latency, cost, error rates).
• Experience with cloud platforms (AWS preferred) and containerized deployments.
• Strong problem-solving skills with a structured, evidence-based approach, comfortable operating in ambiguity and delivering iteratively.