Artificial Intelligence Engineer
First seen by Alion on Oct 7, 2026.
Role : LLM Engineer/AI Engineer
- Location: Rai Durg, Hyderabad
- Work mode- Hybrid model working (3 days work from office)
- Experience: 5 to 8 Years (Minimum 5 years as a LLM/ AI engineer)
- Mandatory Skills: RAG Archiecture, LLM, Open AI, Anthropic, Llama, Mistral, RAG Architecture, Version Tunning, DevOps
- Qualification: Bachelor of Engineering - Bachelor of Technology (B.E./B.Tech.)
- Notice period: Immediate / early joiners (Max. 15-30 days)
- Interview Process: 2-3 Technical rounds
Important Note :
- We are currently prioritizing immediate / early joiners (maximum 15-30 days- notice period above 30 days will be automatically rejected.).
Position Overview :
We are seeking a highly technical LLM/AI Engineer to build, optimize, and deploy the models that power our Agentic AI initiatives. You will be the primary person responsible for ensuring our agents don't just "chat," but execute with precision.
Your focus will be on model selection, prompt engineering at scale, RAG (Retrieval-Augmented Generation) optimization, and ensuring our AI output is grounded in our specific business logic. This role requires a "builder" mentality, someone who can take a raw model and turn it into a production-ready asset that significantly shortens our support cycles
Key Responsibilities :
- Model Engineering: Implement and optimize LLM pipelines using both proprietary (OpenAI, Anthropic) and open-source models (Llama, Mistral) to find the best cost-to-performance ratio.
- RAG Architecture: Build and maintain sophisticated RAG systems to ensure agents have real-time access to our internal documentation, customer history, and trading platform data.
- Prompt Engineering & Tuning: Develop and version-control complex prompt templates, utilizing techniques like Few-Shot prompting and Chain-of-Thought to improve reasoning.
- Evaluation & Testing: Establish "LLM-as-a-judge" frameworks and automated testing to measure hallucination rates, toxicity, and accuracy before agents hit the non-production environments.
- Tool-Use Logic: Program the logic that allows agents to use external tools (APIs, Database queries, Moltbot functions) reliably and safely.
- Latency Optimization: Streamline model inference and data retrieval to ensure the "Super Employee" responds in near real-time, improving customer satisfaction.
- DevOps for AI: Familiarity with LLMOps tools for monitoring model performance and drift in production.
Additional qualifications :
- Experience in high-throughput environments (e.g., Trading, FinTech, or Global Logistics).
- Previous experience building and deploying autonomous agents in a production environment.
- Familiarity with Claude and OpenClaw ecosystem.
Why Join ?
- Opportunity to lead transformative initiatives, modernizing legacy systems and shaping the future of trading technology.
- Work with cutting-edge technologies in a dynamic, fast-paced environment.
- Competitive compensation, professional growth opportunities, and the chance to work with industry-leading experts.
Skills
LLM, Artifact Management, Agentic AI, Prompt Engineering