Lead AI Platform Engineer

What You Will Do

· Design, build, deploy, and support production AI solutions.

· Develop agentic workflows, tool integrations, and orchestration pipelines.

· Build and evolve RAG and agent-based architectures.

· Create evaluation frameworks to improve quality, groundedness, and reliability.

· Implement AI observability, tracing, and monitoring capabilities.

· Develop automated testing and regression validation processes.

· Integrate AI solutions with APIs, enterprise applications, and data sources. Design reusable AI patterns, frameworks, and components that increase platform scalability and team productivity.

· Establish engineering best practices and contribute to code reviews.

· Research and adopt emerging AI technologies where they provide business value.

· Partner with stakeholders to translate business problems into AI solutions

Required Skills

· 5+ years of software engineering experience.

· Proven track record of delivering enterprise-grade production software.

· Strong Python development skills.

· Experience building, deploying, and operating production AI systems.

· Experience designing and implementing RAG solutions.

· Experience with Databricks.

· Hands-on experience with LangGraph or similar agent orchestration frameworks.

· Experience building AI workflows that leverage tools, APIs, and external systems.

· Experience with AI evaluation frameworks and quality measurement.

· Experience implementing AI observability and tracing solutions.

· Understanding of agent architecture patterns, prompt engineering, and LLM evaluation techniques.

· Experience with AWS in production environments.

· Experience designing and consuming REST APIs.

· Experience with Git, CI/CD, and modern software engineering practices.

· Knowledge of secure coding principles and responsible AI practices.

· Experience collaborating within Agile software development teams

Nice to Have

· Experience with AgentBricks.

· Experience with Microsoft Copilot extensibility and agent development.

· Experience with LangChain and related frameworks.

· Experience with MCP integrations.

· Experience with vector databases and semantic search.

· Experience with AWS Bedrock.

· Experience with OpenTelemetry, LangSmith, Grafana, MLflow, DeepEval, or similar tooling.

· Experience deploying multi-agent systems.

· Experience with Terraform.

· AWS, Databricks, Microsoft, or AI-related certifications.

Mindset

· Delivers AI solutions that create measurable business value.

· Treats evaluation and observability as first-class engineering disciplines.

· Balances innovation with reliability, scalability, and governance.

· Takes ownership of production systems and outcomes.

· Thinks holistically about data, architecture, monitoring, and continuous improvement.

· Collaborates effectively across technical and business teams.

· Continuously learns and adapts to evolving AI technologies.