Job Details

Description

As an AI Engineer at 2nd Swing, you'll build production-grade AI systems that automate real work across the business, especially multi-step, tool-calling workflows. This role is ideal for a strong engineer who can ship without AI tools and then use modern AI coding agents (Claude Code, Cursor, Windsurf, etc.) to move faster with control and reliability.

Come work with us, not for us!

2nd Swing Is a One-of-a-kind, Forward Thinking, Customer-centric Golf Retail Company. Our Employees Are Highly Valued While Working Hard In a Positive And Supportive Culture. At 2nd Swing You Will Find

Vast Exposure to the Golf Industry
A Commitment to Total Well-Being
Opportunities to Discover Your Fit and Make an Impact
A Collaborative and Flexible Environment

Position Responsibilities

Design and build multi-step, tool-calling AI workflows (planning, execution, validation, retries) that integrate with internal systems and APIs.
Implement and maintain model routing across providers (OpenAI, Anthropic, Azure OpenAI, and/or open-source/self-hosted models) based on cost, latency, and quality needs.
Convert unstructured data (PDFs, emails, logs, free text, poorly formed CSVs) into AI-ready assets (cleaned datasets, structured schemas, metadata, embeddings, RAG indices).
Build and/or integrate MCP connectors to safely expose tools and data to agentic systems.
Use AI coding agents effectively, set guardrails, and review outputs with strong engineering judgment.
Monitor reliability and quality through evals, regression tests, and observability (logging, tracing, feedback loops).
Stay current with AI technologies as it evolves.

Required Qualifications

Bachelors degreen in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience.
5+ years professional software engineering experience with a strong track record before AI coding agents.
Strong programming ability in Python and/or TypeScript (testing, APIs, debugging, code review).
Built multiple production agentic workflows using tool calling.
Experience working with models from multiple providers.
Proven ability to transform unstructured data into structured, consumable formats.
Keeps up with AI technology on a near-daily basis and can separate signal from hype.

Preferred Qualifications

Built MCP connectors or other tool-integration interfaces used by LLMs in production.
Experience with vector search / RAG systems (pgvector, OpenSearch, Qdrant, Azure AI Search, etc.).
Familiarity with LangChain/LangGraph, Semantic Kernel, or equivalent orchestration patterns.
Familiarity with the game of golf and golf equipment.

Compensation: Our compensation is competitive and personalized, reflecting your specific experience level. The pay range for this role is $106,000 - $186,000.

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