Lead /Principal Gen AI Engineer (Only w2)

Note: Look for Candidate with Google ADK and MCP experience.

Job Description: 

·         We are seeking a Lead Al Engineer to design, build, and scale Agentic and Generative Al solutions that deliver measurable business outcomes.

·         This role is hands-on and includes leading moderately complex initiatives, contributing to large-scale technical strategy, and serving as a technical escalation point while mentoring engineers.

In this role, you will:

• Lead or contribute to moderately complex initiatives and deliverables within Al/ML and software engineering domain environments, with accountability for high-quality outcomes.
• Contribute to large-scale planning of strategies for generative Al capabilities, including platform patterns, engineering standards, and operational readiness.
• Design, code, test, debug, and document Al-enabled services and applications, including upgrades and deployments across environments.
• Design and develop Generative Al applications using large language models (LLMs), retrieval-augmented generation (RAG), and agentic frameworks; integrate Al capabilities into existing enterprise products and systems.
• Build production-grade agentic solution using LangChain and LangGraph combining rapid composition with explicit state-machine orchestration
• Develop agents with Google ADK, leveraging its multi-agent architecture, flexible orchestration, tool ecosystem (including MCP tools), built-in evaluation, and deployment-ready patterns.
• Engineer secure tool execution patterns (service-to-service calls, least privilege, auditability) and align with enterprise approaches to agent-to-agent communication (A2A) and MCP-based tool integration where applicable.
• Evaluate moderately complex technical challenges requiring in-depth assessment of Al technologies, orchestration approaches, model behavior, and enterprise integration patterns.
• Troubleshoot and resolve complex technical issues across Al services and models; ensure monitoring and operational hygiene to improve efficiency and mitigate risk.
• Lead, design, develop, test, and implement application components, tools, utilities, and analytics related to Al lifecycle needs (e.g., evaluation, quality monitoring, model drift monitoring).
• Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals.
• Act as an escalation point, providing guidance and direction to less experienced staff; drive engineering excellence across the team.
• Ensure delivery aligns with policies, procedures, compliance requirements, and risk management expectations for supported areas.