Senior AI Engineer building and deploying AI/ML solutions in production for a consulting firm. Collaborating with engineering and product teams to deliver scalable AI systems and stay updated on AI advancements.
About the role
- AI Engineer designing agent-based frameworks at Thiga, focused on Production-Grade AI and innovative R&D efforts. Collaborating on cutting-edge AI integration and architecture for client projects.
Responsibilities
- Architect Agent Systems: Design agents using tools such as LangGraph or AutoGen.
- Inference Optimization: Experiment with latency/cost/quality trade-offs (quantization, semantic caching, selecting SLM vs LLM models).
- RAG: Implement Retrieval-Augmented Generation approaches.
- Fine-tuning & Local LLMs: Explore self-hosting (vLLM, Ollama) and fine-tuning models on specific datasets.
- Industrialization (LLMOps): Set up robust evaluation pipelines (LLM-as-a-judge, Ragas, DeepEval) to ensure non-regression and factuality.
- Full-stack AI integration: Connect the "brains" (LLMs) to data (APIs, SQL/NoSQL databases, vector stores) via an agent-based approach.
- Architecture audit: Analyze clients' agentic architecture implementations for optimization or redesign.
Requirements
- A passionate Software Engineer with at least 2 years of experience: You are proficient in Python and/or TypeScript. 'Spaghetti' notebook code is not sufficient.
- AI Stack expert: You have hands-on experience with agentic frameworks (LangChain, LangGraph, LlamaIndex, or others) and experience with one or more vector stores (Qdrant, Weaviate, Pinecone, ...).
- Pragmatic and rigorous: You know how to manage hallucination and nondeterminism. You understand the difference between a ReAct agent and chain-of-thought.
- DevOps-aware: You are comfortable deploying agents on one or more platforms (AWS, Google Cloud, Azure, Hugging Face, ...).
Benefits
- An opportunity to build autonomous systems, not just chatbots.
- A technical environment free of legacy AI technical debt.
- A team that values hard tech and clean software engineering.
- The opportunity to define AI design patterns for years to come.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
AI Engineer in Bangalore driving innovation in Generative AI with expertise in RAG pipelines and Frontier Models.
Senior Machine Learning Engineer at TheAppLabb designing and deploying production - grade ML systems with a focus on AI features and cloud infrastructure.
Staff AI Engineer overseeing AI/ML infrastructure for bsport's intelligent features. Collaborating with cross - functional teams to build and maintain robust production systems in a hybrid work environment.
GenAI Developer designing and building production - grade AI systems for Nordic clients. Collaborating with Data and Platform Engineers to deliver end - to - end solutions in various industries.
Junior Applied AI Engineer building intelligent, data - driven HR solutions at Fortinet. Joining the HRIS team to develop AI - powered tools like chatbots and analytics models.
Senior AI Engineer building core AI features for a tax advisory platform. Developing workflows and document intelligence functionalities while collaborating with a dynamic team in a hybrid setting.
Copilot & Viva AI Engineer at the Federal Reserve Bank designing and implementing IT engineering solutions. Collaborating with teams to deploy Microsoft Copilot and manage AI initiatives.
AI Engineer developing production - ready AI features from idea to rollout for Logicc's AI platform in a hybrid work environment.
AI Engineer focusing on low - code platforms, building solutions for clients at Satori Analytics. Collaborating with teams to innovate and implement AI technologies within various industries.