Salary
≈ $34k – $81k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp
First seen by Alion on Oct 23, 2026.
Overview
Company
Impact
Profile match
OrbitronAI is an enterprise AI platform that builds AI agents for enterprises in regulated industries to help automate operations, compliance, supply chain and risk workflows with human oversight and auditability.
Responsibilities:
- Design and deploy cutting-edge AI agents using our orchestration layer built on n8n, Temporal, and next-gen agentic stacks.
- Build intelligent, context-aware workflows that plug directly into enterprise systems — transforming how businesses make decisions, serve customers, and manage operations.
- Prototype fast. Iterate faster. You'll test, fail, learn, and ship production-grade AI agent flows that power real business outcomes.
- Collaborate with product and design to identify high-impact user journeys where AI can be a 10x unlock — and then build them.
- Push the limits of RAG, embeddings, and vector search to bring real-time, grounded intelligence into every agent decision.
- Engineer smart integrations with OpenAI, Anthropic, Claude, and other LLMs — blending in enterprise APIs, CRMs, internal tools, and more.
- Lead development of multi-agent orchestration flows: planner-executor models, memory layers, persona-based behaviours, and tool-using agents.
- Own the AI pipeline end-to-end: prompt engineering, dynamic context handling, agent simulation and evaluation, all the way to deployment and monitoring.
- Help set the bar for reliability, latency, and safety of AI outputs — your work will shape how users trust AI inside their organisations.
- Work alongside curious, driven people who care deeply about shipping transformative products, not just academic demos.
Requirements:
- Bachelor's degree in Computer Science or equivalent practical experience.
- 8+ years of hands-on experience in applied machine learning, NLP, or AI system development, particularly with LLMs and agentic frameworks.
- Deep familiarity with large language models such as GPT-4, Claude, or similar, including prompt tuning, fine-tuning, or API-based deployment.
- Hands-on experience with Retrieval-Augmented Generation (RAG) pipelines using vector stores and embeddings.
- Knowledge of multi-agent systems, task orchestration, and related architectures.
- Proficiency in Python and modern ML frameworks (e. g., PyTorch, TensorFlow).
- Experience integrating with agent orchestration frameworks like LangChain, LangGraph, Temporal, n8n, or custom stacks.
- Solid understanding of enterprise software principles, including version control, CI/CD pipelines, API design, and performance monitoring.
- Excellent communication and collaboration skills; ability to thrive in a fast-paced, startup environment with evolving priorities.
Skills
Claude, GPT-4, LLM, Python, RAG, Retrieval-Augmented Generation, large language models
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