About the Role
LatentBridge is seeking an experienced Sr. AI/ML Engineer to lead the end-to-end design, development, and deployment of enterprise-scale Artificial Intelligence and Machine Learning solutions. In this role, you will architect robust, scalable, and secure AI systems leveraging Generative AI, Large Language Models (LLMs), Agentic AI, and advanced Machine Learning to solve complex business challenges. You will collaborate with cross-functional teams, mentor AI engineers, drive architectural decisions, and deliver production-ready AI solutions that create measurable business impact.
If you're passionate about building next-generation AI platforms and leading innovation in enterprise AI, we'd love to hear from you.
Key Responsibilities
- Architect and develop scalable AI/ML solutions for enterprise applications.
- Design and implement production-grade Generative AI and LLM-powered solutions using modern AI frameworks.
- Build, deploy, and optimize Retrieval-Augmented Generation (RAG) systems, AI Agents, and multi-agent workflows.
- Lead the development, deployment, monitoring, and continuous optimization of ML pipelines and LLM applications in production.
- Design robust backend services and APIs using Python and FastAPI for AI-powered applications.
- Implement semantic search and knowledge retrieval using Vector Databases such as Pinecone, ChromaDB, FAISS, Qdrant, or Azure AI Search.
- Collaborate with product managers, business stakeholders, and global clients to translate business requirements into scalable AI solutions.
- Mentor junior and mid-level AI engineers through technical guidance, code reviews, and knowledge sharing.
- Drive AI best practices, documentation standards, model evaluation, observability, and deployment excellence.
- Troubleshoot complex AI/ML systems and continuously improve model performance, scalability, and reliability.
- Stay up to date with emerging AI technologies and recommend innovative solutions to improve products and processes.
- Required Skills & Experience 6–8 years of professional experience in Artificial Intelligence, Machine Learning, Data Science, or Software Engineering.
- Strong expertise in Python and backend development.
- Hands-on experience building production-grade Generative AI applications.
- Strong experience working with Large Language Models (LLMs) such as GPT, Claude, Llama, Gemini, or similar foundation models.
- Experience building Retrieval-Augmented Generation (RAG) applications for enterprise use cases.
- Strong knowledge of LangChain, LangGraph, AI Agents, and Agentic AI workflows.
- Experience with Prompt Engineering, embeddings, semantic search, and Vector Databases.
- Hands-on experience with FastAPI or Flask for AI application development.
- Strong experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, Kubernetes, CI/CD, and cloud-native deployments.
- Experience working with SQL and NoSQL databases.
- Strong understanding of AI system design, scalability, security, and production deployment.
- Excellent analytical, communication, leadership, and stakeholder management skills.
Preferred Skills
- Experience with fine-tuning LLMs using techniques such as LoRA, QLoRA, or PEFT.
- Exposure to AI observability and LLMOps tools such as LangSmith, Langfuse, MLflow, Arize, or similar platforms.
- Experience with Infrastructure as Code (Terraform) and cloud automation.
- Knowledge of Apache Airflow, orchestration frameworks, and scalable ML pipelines.
- Experience implementing AI guardrails, hallucination mitigation, and Responsible AI practices.
- Experience working with enterprise clients in the US or Europe.
- Exposure to OCR, Document Intelligence, Knowledge Graphs, or multimodal AI is an added advantage.
