Generative AI Engineer

Job Title: GenAI Technical Lead

Role Overview:

We are seeking a senior, hands-on AI Technical Lead to join Global GenAI Automation team. This role combines deep AI and agentic systems expertise with strong software engineering, DevOps, and technical leadership skills to design, build, and deliver scalable AI solutions. You will bridge strategy and execution ensuring AI initiatives are technically sound, production-ready, and aligned with business goals, while mentoring engineers and driving engineering excellence across the team.

Responsibilities and Key outcomes

• Lead Technical Delivery of Agentic AI Solutions: Own the end-to-end technical delivery of AI agent systems from architecture and design through implementation, testing, and production deployment ensuring solutions are robust, scalable, and maintainable.
• Define & Drive AI Architecture: Establish and evolve the technical architecture for agentic AI services, making long-term design decisions and trade-offs across data, AI models, APIs, and cloud platforms in alignment with enterprise standards.
• Engineer Production-Grade AI Systems: Contribute hands-on to the codebase, designing clean architectures, building agentic orchestration pipelines, and implementing integrations with enterprise systems (SAP, Salesforce) using Python, FastAPI, LangGraph, and Microsoft Agent Framework.
• Own DevOps & Production Readiness: Build and maintain CI/CD pipelines, cloud infrastructure (Azure, AKS, Docker), and observability stacks (monitoring, logging, OpenTelemetry) to ensure every AI deployment is reliable, secure, and auditable.
• Drive Standards & Engineering Excellence: Champion software engineering best practices code quality, testing, documentation, and collaborative development and contribute to agentic standards (MCP, A2A) and reusable platform components.
• Mentor & Lead Engineers: Guide and mentor software engineers through code reviews, architectural discussions, and hands-on pairing, fostering a culture of technical excellence and continuous learning.
• Manage Delivery & Stakeholders: Plan, estimate, and track delivery of AI initiatives, managing scope, risks, and dependencies while collaborating effectively with business, product, and engineering stakeholders.

Education and Work Experience

• Master's degree + 5 years or Bachelors Degree + 7 years of industry experience, or PhD + 2 years of industry experience.
• Background in Computer Science, Computer Engineering, IT, or a related field.
• Industry and delivery experience prioritized over purely academic roles.

Technical & Professional Knowledge:

• AI & Intelligent Systems Expertise: 3+ years of hands-on experience working with AI in production environments. Strong practical knowledge of AI agents, agent-based systems, model integration, orchestration, and lifecycle management. Ability to translate AI capabilities into real business value.
• Software Engineering: Proven experience as a software developer with strong coding skills in Python (Pydantic, FastAPI). Solid understanding of clean architecture, code quality, testing, documentation, and version control. Capable of mentoring engineers and leading code reviews.
• Architecture & Technical Vision: Proven ability to define and drive an AI architecture vision. Experience designing scalable, secure, and maintainable AI systems. Strong systems thinking across data, AI models, APIs, and cloud platforms.
• DevOps & Production Readiness: Proven experience in DevOps engineering for AI-enabled systems. Hands-on experience with CI/CD pipelines, cloud infrastructure and containerization (Azure, AKS, Docker), and monitoring/logging/reliability tooling.
• Project & Delivery Leadership: Experience in project management including planning, estimation, and delivery tracking. Involved in projects both as project manager and hands-on developer. Strong ownership mindset managing scope, risks, and dependencies.

Nice to Have

• Experience with multi-agent architectures, MCP, and A2A (Agent-to-Agent) protocols.
• Familiarity with LangGraph, LangChain, or Microsoft Agent Framework.
• Experience with Databricks / Unity Catalog for large-scale data context.
• OpenTelemetry and distributed tracing experience.
• Exposure to enterprise integration patterns (SAP, Salesforce).

Tech Stack

• Languages: Python (Expert), TypeScript (Plus).
• Frameworks: LangGraph, LangChain, FastAPI, Pydantic, Microsoft Agent Framework.
• Infrastructure: Azure (AKS, AI Foundry, Functions), Docker, Redis, PostgreSQL.
• AI/LLM: OpenAI, Anthropic, Mistral, Azure AI Services.
• Standards: MCP, A2A, OpenTelemetry.
• DevOps: Git, CI/CD, monitoring & observability tooling.

Key Personal Attributes

• Strong analytical and problem-solving skills.
• Ability to balance strategic leadership with hands-on execution.
• Clear communicator across technical and non-technical audiences.
• Leadership mindset with mentoring capabilities.
• Results-driven and delivery-focused.

Proven ability to collaborate effectively across international, multicultural teams in a global environment