Machine Learning Engineer - Agentic AI

About Truxt Truxt.ai is an early stage, cutting-edge startup building Autonomous Software Intelligence Analytics platform, powered by AI and Generative AI. We're seeking passionate Machine learning Engineer to join our journey.

Job Description: This is an exciting opportunity to build a state-of-the-art autonomous system that combines Agentic AI, Model Context protocol (MCP ) Retrieval-Augmented Generation (RAG), Prompt Engineering, multiple Large Language Models (LLMs), Knowledge Graphs, and real-time web data integration.

As our Machine Learning Engineer, you'll be at the forefront of , designing and implementing an advanced platform that leverages the latest in natural language processing and knowledge representation. Agents that don't just flag issues, they act.

NOTE: This will be a really difficult role where you'll have to learn and implement the latest evolving AI technologies. Please do NOT apply for this role if you: Want a 9-5 job Cannot take ownership Are not ready to commit 9-9-6 per week Do not have startup Builder(get it done) mentality

Responsibilities: End-to-end agentic execution pipelines that take action Multi-agent orchestration systems using LangGraph, AutoGen, CrewAI, or custom tool-use loops, with planning, reflection, and tool-calling built in Architect and develop a Agents, MCP Integrations, RAG-based system multiple specialized LLMs Create efficient algorithms for semantic search and context aggregation Develop systems for real-time web data integration and processing Implement and optimize multi-LLM orchestration strategies Design and implement Knowledge Graph Ensure data security and privacy throughout the platform Collaborate with clients to curate and maintain the knowledge base Continuously improve system performance through feedback loops and metrics analysis

Requirements: Bachelor’s degree in Computer Science, Machine Learning, or a related field. 2+ years of experience in machine learning, with a focus on NLP or LLMs Ideally 3–6 years of ML/AI engineering experience, you've shipped models and agents to production, not just Jupyter notebooks Strong knowledge of Knowledge Graph technologies and graph databases Proficiency in Python and experience with ML frameworks (PyTorch, TensorFlow) Experience with web scraping, API integrations, and data processing pipelines Excellent problem-solving skills and attention to detail

Preferred Qualifications: Experience with multi-model AI systems and model orchestration Familiarity with MLOps practices and tools Knowledge of information retrieval techniques and search algorithms Experience with cloud platforms ( Azure, GCP or AWS) Contributions to open-source NLP or ML projects

What Makes This Opportunity Different: Freedom to Execute: Set your own goals, timelines, and approaches without bureaucratic hurdles. True Ownership: Founding engineers receive substantial equity packages (competitive with senior engineer salaries at scale), ensuring you directly benefit from the value you create. Technical Challenge: Solve complex real-world problems with meaningful impact. Impact-Driven Culture: Directly influence product direction, company culture, and growth strategy. Transparent Leadership: Collaborative environment, weekly strategy sessions, and full visibility into company health and roadmap. Good Equity