Senior AI Engineer

We are looking for a Senior AI Engineer to design, build, and deploy high-quality AI-powered features with end-to-end ownership, delivering scalable and impactful AI solutions.

Experience

10+ Years

Location

Remote

Responsibilities End-to-End AI Feature Ownership

Design and implement AI-powered features (LLM workflows, copilots, and agent-based systems with tool use and multi-step reasoning).

Own the full lifecycle: prototyping evaluation production deployment iteration.

Ensure solutions are reliable, performant, and aligned with product needs.

AI System Implementation

Build and optimize prompt pipelines for specific use cases.

Build retrieval systems (embeddings, chunking, ranking).

Implement RAG-based workflows where needed.

Iterate on outputs to improve quality, accuracy, and consistency.

Design scalable and cost-efficient AI architectures for production workloads.

Select and evaluate models (hosted vs. open-source) based on use-case constraints.

Agent-Based Systems (AgentCore)

Design and build agentic workflows capable of multi-step reasoning and decision-making.

Integrate agents with tools, APIs, and internal systems to perform real-world actions.

Implement planning, execution, and reflection loops for complex tasks.

Manage context, memory, and state across multi-step interactions.

Balance deterministic workflows vs. agent autonomy for reliability and control.

Experimentation & Evaluation

Run structured experiments to compare approaches (prompting, retrieval, models).

Define and track key metrics for AI performance (quality, latency, cost).

Debug and improve non-deterministic system behavior.

Build and maintain evaluation datasets and benchmarks.

Implement automated evaluation pipelines for continuous improvement.

Collaboration & Contribution

Drive technical direction and influence AI adoption across teams.

Partner with product managers and designers to scope AI features.

Contribute to shared patterns and reusable components.

Participate in code reviews and design discussions.

Support and mentor mid-level engineers where needed.

AI Reliability, Safety & Governance

Design guardrails to ensure safe and reliable AI behavior.

Mitigate hallucinations, prompt injection, and model misuse.

Ensure compliance with data privacy and enterprise requirements.

Implement monitoring and observability for AI systems in production.

Implement guardrails for agent actions (tool access control, execution boundaries).

Prevent failure cascades in multi-step agent workflows.