BigCommerce is building a new team to deliver a suite of conversational AI agents spanning the B2B commerce lifecycle — Product Discovery, Pricing & Quoting, Order Automation, Fulfillment & Delivery, and Post-Sale Support. The agents are built in Go on Google ADK with Gemini, with evaluation infrastructure in Braintrust and a streaming AG-UI frontend.
As a Senior Backend Engineer specializing in AI agents, you will design the agents themselves: orchestration, sub-agent architecture, tool integration, prompt engineering, and — critically — the evaluation discipline that determines whether these agents are trustworthy enough to ship. Agent quality in this domain is won on evals, not just code, and you will own that practice for the team.
What You’ll Do
- Design, build, and iterate on AI agents in Go/Python using an orchestrator/sub-agent architecture, covering intent interpretation, delegation, and safe action execution
- Own eval-driven development: build and maintain golden datasets, scorers, and regression suites (Braintrust or similar) for critical quality metrics such as discovery recall and quote accuracy
- Develop and refine prompts, model configurations; treat prompts and model settings as versioned, tested artifacts
- Integrate agents with MCP servers and backend tools, defining safe tool-call contracts, approval flows for write actions, and guardrails against prompt injection and abuse
- Instrument agents with tracing, metrics, and cost tracking; use production signals to drive quality improvements
- Collaborate with product designers and frontend engineers to deliver intuitive, useful conversational experiences
- Quickly build proof-of-concept agents to validate user stories, then harden them to GA quality
- Drive architecture decisions on ambiguous problems and mentor other engineers in agent engineering practices
Who Are You
- 5+ years of experience in backend or full-stack software development, with hands-on experience building agentic AI/LLM applications
- Education: Preferred minimum Bachelor's degree in CS, EE, SW, CE, MIS; or equivalent experience
- Strong and proven development skills in any major language (Go/Python/Ruby/PHP)
- Experience working with LLMs (Gemini, Anthropic, OpenAI, etc.) in production systems
- Experience with LLM evaluation: building datasets, defining scorers/metrics, and using eval results to drive iteration
- Strong understanding of prompt engineering, tool/function calling, and agent orchestration patterns
- Deep experience designing and building APIs (gRPC, GraphQL, REST) and integrating data across systems
- Hands-on experience building MCP servers or LLM tool integrations
- Excellent problem-solving skills and ability to work in a fast-paced, exploratory environment
- Strong collaboration and communication skills in cross-functional teams
- Strong preference toward execution and delivery
Preferred:
- Experience with agent frameworks (Google ADK, LangChain/LangGraph, Semantic Kernel, or similar)
- Experience with evaluation/observability platforms (Braintrust, LangSmith, or similar)
- Experience with RAG systems and retrieval quality tuning
- Experience with e-commerce platforms or SaaS product development
- Background in conversational AI or natural language processing
Work Where You Thrive
For candidates based in the Austin or Atlanta metro area, the position follows a hybrid work model with three days per week in the office, balancing focused individual work with meaningful in-person collaboration.
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(Pay Transparency Range: $116,000.00 - $195,000.00)
Compensation Transparency
The national base salary range for this role is posted above in this job post.
Final compensation will be determined based on factors such as relevant experience, skills, qualifications and geographic location. We also consider internal equity to help ensure fair and consistent pay practices across our teams.
Where applicable, this role may also be eligible for variable compensation (such as bonus or commission), equity, and benefits in accordance with local policies. Details will be shared during the hiring process. We are committed to equitable and transparent pay practices that align to market data, internal equity, and individual contribution.
