Job VC
AI-Native Engineer. Context Engineering, SDLC Intelligence
Technologies
Description
Trinetix
is looking for a skilled
AI-Native Engineer.
We are building an AI-native ecosystem that will power both our internal SDLC and the next generation of AI-driven solutions for our clients. Our R&D organization is developing context-aware AI agents, intelligent engineering tools, and graph-based knowledge systems that integrate directly into real development workflows.
This initiative will reshape how software is planned, built, tested, and evolved—unlocking entirely new capabilities for our teams and our clients’ product engineering organizations.
Requirements
Hands-on experience building RAG systems, vector search, or semantic pipelines.
Familiarity with knowledge graphs (Neo4j, RDF, property graphs, graph DBs).
Experience working with LLM APIs (OpenAI, Anthropic, Gemini, Llama, etc.).
Understanding of embeddings, text processing, chunking strategies, and retrieval optimization.
Experience building developer tooling, internal tools, plugins, or automation.
Ability to design and prototype systems independently.
Nice-to-Have
Experience building agentic systems (AutoGen, LangGraph, crewAI, smolagents, function-calling agents, etc.).
Experience implementing GraphRAG or similar graph-structured retrieval approaches.
Familiarity with AI-powered SDLC tools (copilots, code intelligence, static analysis via LLM).
Understanding of software architecture and system design.
Experience with CI/CD pipelines, DevOps tooling, or platform engineering.
Ability to create ontologies or domain data models.
Experience working in R&D would be preferable.
Core Responsibilities
Designing the core models and abstractions that will underpin our AI-native engineering ecosystem.
Developing intelligent mechanisms to surface the right information at the right time.
Creating assistive capabilities that streamline engineering tasks and workflows.
Driving innovation in how software teams interact with knowledge, context, and automation.
Collaborating across the organization to embed AI into the end-to-end delivery process.
What We Offer
Opportunity to build a first-of-its-kind AI-native SDLC environment
Chance to influence engineering workflows across the entire company
Work within a high-impact, exploratory R&D team
Competitive compensation and growth opportunities
Full autonomy to prototype, test, and implement ideas
Professional training and English/Spanish language classes
Comprehensive medical insurance
Mental health support
Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more
Flexible working hours
Inclusive and supportive culture
is looking for a skilled
AI-Native Engineer.
We are building an AI-native ecosystem that will power both our internal SDLC and the next generation of AI-driven solutions for our clients. Our R&D organization is developing context-aware AI agents, intelligent engineering tools, and graph-based knowledge systems that integrate directly into real development workflows.
This initiative will reshape how software is planned, built, tested, and evolved—unlocking entirely new capabilities for our teams and our clients’ product engineering organizations.
Requirements
Hands-on experience building RAG systems, vector search, or semantic pipelines.
Familiarity with knowledge graphs (Neo4j, RDF, property graphs, graph DBs).
Experience working with LLM APIs (OpenAI, Anthropic, Gemini, Llama, etc.).
Understanding of embeddings, text processing, chunking strategies, and retrieval optimization.
Experience building developer tooling, internal tools, plugins, or automation.
Ability to design and prototype systems independently.
Nice-to-Have
Experience building agentic systems (AutoGen, LangGraph, crewAI, smolagents, function-calling agents, etc.).
Experience implementing GraphRAG or similar graph-structured retrieval approaches.
Familiarity with AI-powered SDLC tools (copilots, code intelligence, static analysis via LLM).
Understanding of software architecture and system design.
Experience with CI/CD pipelines, DevOps tooling, or platform engineering.
Ability to create ontologies or domain data models.
Experience working in R&D would be preferable.
Core Responsibilities
Designing the core models and abstractions that will underpin our AI-native engineering ecosystem.
Developing intelligent mechanisms to surface the right information at the right time.
Creating assistive capabilities that streamline engineering tasks and workflows.
Driving innovation in how software teams interact with knowledge, context, and automation.
Collaborating across the organization to embed AI into the end-to-end delivery process.
What We Offer
Opportunity to build a first-of-its-kind AI-native SDLC environment
Chance to influence engineering workflows across the entire company
Work within a high-impact, exploratory R&D team
Competitive compensation and growth opportunities
Full autonomy to prototype, test, and implement ideas
Professional training and English/Spanish language classes
Comprehensive medical insurance
Mental health support
Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more
Flexible working hours
Inclusive and supportive culture