You are a hands-on AI learning engineer and collaborative problem solver who enjoys solving ambiguous business problems with AI, creating robust, production-ready solutions. You are comfortable working across the stack—from data pipelines and infrastructure to APIs and monitoring—and partnering directly with forward-deployed engineers, data engineers, platform engineers, and business stakeholders. You thrive in an outcomes-driven environment and want to help build something from the ground up
Experience building reusable accelerators, modular codebases, or products deployed across multiple clients
Industry experience building AI/ML solutions in life sciences, retail, financial services, or manufacturing
Prior experience working in global or remote teams and partnering across US, LATAM, and/or India
Contributions to open source projects, technical communities, speaking engagements, or technical writing related to AI and agents are a plus
A Master’s or other advanced degree in data science, computer science, or a related field
4+ years of experience in AI/ML engineering, software engineering, or data engineering roles building and deploying AI/ML solutions to production
Recent hands-on experience with LLM-powered or agentic applications
Hands-on understanding of Large Language Models, agentic architectures, and retrieval frameworks (RAG), including prompt design, context engineering, and tool/function calling
Experience with LLM orchestration frameworks (e.g. LangChain, LlamaIndex) and the broader agentic stack, such as multi-agent patterns, memory, planning, and protocols (e.g. MCP)
Experience designing evaluation, guardrail, and observability strategics for LLM and agent systems (LLMOps/AgentOps)
Hands-on experience in modern programming languages, such as Python, including developing APIs
Deep expertise in cloud-native AI/ML platforms (e.g. AWS Bedrock and SageMaker, Azure AI/ML, Snowflake Cortex) with proven experience deploying solutions into production
Complete software development lifecycle experience including design, documentation, implementation, testing, deployment, and ongoing operations
Demonstrated use of AI-assisted development tooling to accelerate delivery while maintaining quality
Strong working knowledge of SQL, including writing, debugging, and optimizing complex and distributed queries
Experience delivering projects for external or internal clients in a professional services, product, or consulting environment
Ability to break down complex problems into structured, actionable steps and drive them through to completion, ideally in a fixed-bid capacity
Strong written and verbal communication skills in English, including the ability to explain technical concepts to both technical and non-technical audiences
Proven experience presenting solutions and working directly with internal and/or external clients