Machine learning Engineer

Apps Associates

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Job Description

Job Description

Deep experience with agentic platforms
Hands-on experience building and deploying agents using platforms such as AgentCore, Gemini Enterprise, and Azure Copilot.
Strong understanding of agent SDKs and frameworks such as ADK, LangChain, and Strands.
Strong development workflow discipline
Proficient in modern development workflows (branching, code review, CI/CD, testing, observability).
Clear understanding of why “vibe coding” (coding without specs, tests, or structure) is harmful at scale.
Experience using spec-driven development or similar frameworks to design and implement features in a structured way.
Agentic protocols, communication, and tactics Familiarity with key agentic patterns and protocols such as A2A (agent-to-agent communication), MCP (Model Context Protocol), RAG (Retrieval-Augmented Generation), memory management, and context management.
Ability to design effective interaction patterns between agents, tools, and users.
Cross-functional collaboration
Ability to work with engineers, PMs, and other stakeholders to understand their problems and define clear, actionable requirements.
Experience running workshops, training sessions, and demos to drive adoption and teach best practices.
Hands-on build experience with LLM tooling Have created and maintained Cursor commands, Claude skills, steering documents, and CI agents (or similar equivalents in other tools).
Comfortable experimenting with and standardizing new agent workflows and tools for wider team use.
Nice to have
Experience with enterprise AI governance, safety, and compliance practices.
Background in developer experience (DevEx), platform engineering, or internal tools.
Familiarity with observability and monitoring for agents (traces, logs, evaluation frameworks, feedback loops).
Experience integrating agents with existing systems via APIs, webhooks, and event-driven architectures.