# Senior Lead Generative AI Engineer (Individual Contributor)

## Role Summary

We are hiring a senior individual contributor to design, build, and productionize end-to-end agentic AI systems for high-impact enterprise workflows. This role is for a hands-on builder who can own architecture, coding, evaluation, reliability, and deployment at scale.

You will work on complex AI programming problems that require deep engineering judgment across multi-agent orchestration, MCP integrations, secure tool usage, retrieval systems, and cloud deployment.

## Why This Role Is Different

- You will own the full lifecycle: problem framing, architecture, implementation, deployment, observability, and continuous optimization.

- You will work on hard, real-world AI systems where accuracy, latency, reliability, and governance matter together.

- You will influence engineering quality standards across agent design, LLMOps, and production guardrails while remaining a strong individual contributor.

## Core Responsibilities

- Build end-to-end agentic AI systems from scratch using robust software engineering and AI systems design principles.

- Design and implement multi-agent workflows (planner, executor, reviewer, verifier, fallback) with clear control flows and reliability mechanisms.

- Build and integrate MCP-compatible tool ecosystems, including secure access controls, tool permissioning, and auditable execution patterns.

- Architect and optimize RAG pipelines with vector databases, structured retrieval, reranking, and context management.

- Define and enforce output quality standards using schema-driven generation, validation layers, and guardrails.

- Establish evaluation pipelines for correctness, groundedness, robustness, cost, and latency.

- Lead cloud-native deployment and runtime optimization on AWS or Azure, including scalable inference and operational monitoring.

- Drive incident triage and production debugging for agentic workflows.

- Translate business goals into AI system designs with measurable outcomes.

- Mentor junior engineers through design reviews, code reviews, and problem decomposition.

## Must-Have Technical Skills

- 9 to 12 years of software engineering experience with advanced Python expertise.

- Strong command of software design patterns and architecture for complex distributed systems.

- Working depth in deep learning foundations: neural networks, transformers, embeddings, and modern LLM behavior.

- Proven experience building and shipping production agentic AI systems, not only prototypes.

- Proven experience with multi-agent orchestration frameworks and patterns.

- Proven experience implementing MCP server-client integrations in secure enterprise contexts.

- Strong RAG engineering skills with vector databases and retrieval quality tuning.

- Hands-on LLMOps capability: experiment tracking, evaluation frameworks, model monitoring, and release governance.

- Strong prompt, context, and harness engineering capability for high-fidelity outputs.

- Strong understanding of data security and governance controls for AI systems.

## Preferred Skills

- Proficiency in additional programming languages beyond Python.

- Experience with advanced inference optimization (for example multi-GPU sharding, quantization, hardware-specific runtimes).

- Experience with enterprise integration patterns across APIs, data platforms, and workflow systems.

- Experience with financial or document-intelligence style structured extraction systems.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Senior Lead Generative AI Engineer (IC)

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