AI-Native Engineer. Context Engineering & SDLC Intelligence at Trinetix

Bucharest, , Romania -

Full Time

Start Date

Immediate

Expiry Date

27 Feb, 26

Salary

0.0

Posted On

29 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

RAG Systems, Vector Search, Semantic Pipelines, Knowledge Graphs, LLM APIs, Embeddings, Text Processing, Chunking Strategies, Retrieval Optimization, Developer Tooling, Automation, System Design, CI/CD Pipelines, DevOps Tooling, GraphRAG, Agentic Systems

Industry

IT Services and IT Consulting

Description

Location: Remote or Hybrid Trinetix is looking for a skilled AI-Native Engineer (Context Engineering & SDLC Intelligence) 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. 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 About Us Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world. Headquartered in Nashville, Tennessee, we have a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. We partner with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture. Our operations are driven by a strong business vision, a people-first culture, and a commitment to responsible growth. We actively give back to the community through various CSR activities and adhere to international principles for sustainable development and business ethics. To learn more about how we collect, process, and store your personal data, please review our Privacy Notice: https://www.trinetix.com/corporate-policies/privacy-notice

Responsibilities

Designing core models and abstractions for the AI-native engineering ecosystem. Developing intelligent mechanisms to surface relevant information and streamline engineering tasks.