AI-Native Fullstack Engineer - Tech Lead

Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world. Headquartered in Nashville, Tennessee, it has a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. The company partners with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture.

• Proven technical leadership experience including team leadership or ownership of major workstreams, setting technical direction, and shipping through others.
• Strong fullstack engineering skills with production experience in at least two of C#, Python, and JavaScript/TypeScript, and ability to pick up the third.
• Hands-on experience building AI-native products powered by LLMs, including prompting, retrieval-augmented generation, agents, and evaluations.
• Self-directed and motivated, able to thrive with ambiguity and drive problems to results.
• Cloud experience (AWS, Azure, or GCP) and DevOps skills sufficient to deploy and demo prototypes, including CI/CD and containers.
• Valued but not required: understanding of ETL/ELT, data warehouses, lakehouse concepts, and data engineering depth.

Nice to have:

• Experience taking a 0→1 product or prototype to real users or market validation.
• Specialty in distributed systems, ML/AI, frontend architecture, or data engineering.
• Background in startup, R&D lab, or innovation team with emphasis on speed and ownership.
• Familiarity with experiment design and rapid user testing for idea validation.

• Own the technical vision and execution for a portfolio of proofs of concept, from initial research through working prototype.
• Lead a small engineering team by setting direction, reviewing work, growing people, and maintaining focus and motivation.
• Run lightweight research including problem scoping, landscape survey, hypothesis formation, and defining success criteria for prototypes.
• Translate ambiguous ideas into concrete plans with clear milestones and execute against them.
• Build fullstack solutions including backend services, frontends, data pipelines, and integration.
• Use AI tooling to accelerate development and build products embedding LLMs, agents, retrieval, and related AI techniques.
• Make pragmatic build-versus-buy decisions balancing speed and quality for proofs of concept.
• Partner with product, design, and leadership to decide which prototypes graduate to products.