Senior AI Agent Engineer

# Senior AI Agent Engineer ## Company Overview *Not specified.* ## Job Summary We are seeking an **experienced engineer** to **design and build secure, production-grade AI agents** that seamlessly integrate with business systems. The role involves developing agents capable of retrieving trusted information, utilizing tools, and supporting human-approved workflows. The successful candidate will contribute to advancing AI capabilities within the organization, ensuring robust, safe, and efficient AI operations in production environments. ## Responsibilities - Build and operate the **AI-agent runtime**, ensuring reliable and scalable performance. - Design **coordinator and specialist-agent workflows** to optimize task execution and collaboration. - Create **typed and versioned tool registries** for consistent and maintainable integrations. - Integrate agents with **backend services and data sources** to enable comprehensive data access. - Implement **conversation state management** and purpose-bound memory to support contextual interactions. - Develop **Retrieval-Augmented Generation (RAG)** ingestion, retrieval, provenance, and citation systems. - Implement **deterministic authorization and policy controls** outside the AI models to enforce security and compliance. - Incorporate **human confirmation** steps for actions with significant impact. - Build **evaluation suites** and **automated release gates** to ensure quality and safety. - Establish **observability, latency, and cost controls** for operational efficiency. - Implement **feature flags, kill switches, and graceful degradation** mechanisms. - Support **security reviews, production deployment, and incident response** procedures. - Own **canary releases, rollback procedures**, and maintain operational runbooks for smooth deployment and maintenance. ## Qualifications - **Strong Python engineering experience** with expertise in async Python, FastAPI, Pydantic, SQLAlchemy, and Alembic. - Proven **production experience with LangGraph, OpenAI Agents SDK**, or comparable agent frameworks. - Deep understanding of **Retrieval-Augmented Generation (RAG), embeddings, vector databases** (e.g., pgvector), and source-grounded generation. - Hands-on experience with **PostgreSQL, Redis**, and **queue-based asynchronous background processing**. - Knowledge of **REST APIs, Server-Sent Events**, and distributed system fundamentals such as **idempotency, retries, and timeouts**. - Experience with **model-provider integration** platforms like **OpenAI, AWS Bedrock**. - Skills in **model routing, fallbacks, context management, and prompt versioning**. - Ability to manage **token, latency, and cost controls** effectively. - Proficiency in **OAuth2, JWT, JWKS**, and **service-to-service authentication**. - Expertise in **PII minimization, encryption, secrets management**, and **least-privilege access**. - Experience with **Docker** and **cloud deployments**, preferably on **AWS**. - Familiarity with **OpenTelemetry, structured logging, metrics, tracing, and alerting**. - Strong background in **automated testing** using **pytest** and managing **integration-test environments**. ## Preferred Skills - Experience in **AI safety and evaluation**, including **regression testing, deterministic evaluation, and prompt-injection testing**. - Familiarity with tools such as **DeepEval, RAGAS, Promptfoo** or equivalent. - Knowledge of **adversarial and multilingual testing**. - Experience in **regulated or high-trust domains** is advantageous. - Ability to design **evaluation datasets** and **deployment gates**. - Understanding that **model tool selection** is distinct from **authorization**. ## Experience - **7+ years of software engineering experience**. - **2+ years building generative AI or large language model (LLM) systems**. - Proven track record of **deploying tool-using or RAG-based AI applications** to production. - Strong background in **backend and distributed systems fundamentals**. - Experience in **moving AI products from prototype to monitored production environments**. ## Environment - The role involves working in a **collaborative, fast-paced environment**. - Likely involves **remote, in-office, or hybrid work settings**. - Requires adherence to **security protocols** and **incident response procedures**. - Focus on **high-trust, regulated domains** may involve additional compliance and security considerations. ## Salary *Not specified.* ## GrowthOpportunities *Not specified.* ## Benefits *Not specified.*