Job Description
Are you ready to architect the future of autonomous intelligence? OmniLogic Systems is seeking a visionary Senior AI Engineer to lead the development of our next-generation Agentic AI ecosystem. As we look toward the cutting edge of technology in 2026 and beyond, we are building systems that don't just process data—they act.
In this role, you will move beyond simple chatbots to build complex, multi-agent systems capable of autonomous reasoning, planning, and execution. You will work at the intersection of LLMs, reinforcement learning, and distributed systems, directly impacting how businesses operate in a post-AGI world.
Why Join Us?
- Work on high-impact projects that define the roadmap for 2026.
- Competitive compensation package including equity and benefits.
- Collaborate with top-tier researchers and engineers in a state-of-the-art facility.
Responsibilities
- Architect Agentic Workflows: Design and implement complex multi-agent systems using LangChain, AutoGPT, or custom frameworks to enable autonomous problem-solving.
- LLM Integration: Integrate and fine-tune Large Language Models to enhance reasoning capabilities and reduce hallucination rates.
- Evaluation & Safety: Develop rigorous evaluation pipelines (RLHF, red-teaming) to ensure agent reliability, safety, and alignment with human values.
- System Optimization: Optimize inference latency and cost-effectiveness for high-volume, autonomous deployments.
- API Development: Build robust REST/gRPC APIs that allow external systems to safely interact with autonomous agents.
- Mentorship: Guide junior engineers and contribute to the technical vision of the AI department.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Experience: 5+ years of professional software engineering experience with at least 3 years in AI/ML or LLM application development.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Deep experience with vector databases (Pinecone, Milvus, Weaviate).
- Frameworks: Strong understanding of LangChain, LlamaIndex, or similar orchestration frameworks.
- Algorithmic Knowledge: Solid grasp of search algorithms, game theory, or reinforcement learning concepts.
- Communication: Ability to translate complex technical concepts into clear, strategic narratives for stakeholders.