Identify and prioritize AI use cases; define success metrics and ROI.
Rapidly prototype with LLMs and traditional ML; iterate based on user feedback.
Build data pipelines (ETL), prompt flows/agents, and inference endpoints.
Integrate AI apps with internal tools (APIs, webhooks, RPA) and enterprise systems.
Productionize: testing, evaluation, monitoring, guardrails, and cost/perf tuning.
Documentation, enablement, and training; drive adoption and change-management.
Ensure data privacy, security, and compliance with company policies.
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3-6+ years in software/ML/automation; strong Python/JS and API experience.
Practical experience with LLM platforms (OpenAI, Azure, etc.), vector stores, and prompt engineering/evaluation.
Comfort with data workflows: SQL, ETL, basic analytics; cloud basics (AWS/Azure/GCP).
Experience integrating third-party services (webhooks, REST, OAuth), and deploying apps (Docker/CI/CD).
Clear communicator who can translate business needs into technical plans.
Job Type: Full-time
Work Location: In person
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