# 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.*