Senior AI/ML Developer

Role Overview

We are seeking Senior AI/ML Developers with 7+ years of software engineering and machine learning experience to join an enterprise AI initiative. The ideal candidates have strong hands-on experience building LLM-powered applications, RAG architectures, AI agents, and production-grade ML solutions.

Key Responsibilities

Design, develop, and deploy production-grade AI/ML applications.

Build and optimize LLM-based applications using models such as Claude, GPT, and other foundation models.

Design and implement Retrieval-Augmented Generation (RAG) solutions.

Develop document ingestion, chunking, embedding, vector search, retrieval, and reranking pipelines.

Build AI agents and intelligent workflows using modern agentic AI frameworks.

Integrate LLMs with enterprise applications, APIs, databases, and data platforms.

Develop prompt engineering and evaluation strategies to improve accuracy, reliability, and performance.

Implement model evaluation, monitoring, guardrails, and responsible-AI practices.

Develop scalable Python-based services and APIs.

Work with cloud AI/ML services and containerized environments.

Collaborate closely with AI/ML architects, data engineers, cloud engineers, and business stakeholders.

Troubleshoot performance, latency, scalability, and production issues.

Required Qualifications

7+ years of professional software engineering and/or ML engineering experience.

Strong Python development experience.

Hands-on experience with LLMs and Generative AI.

Strong experience with RAG architectures and vector databases/search.

Experience working with Claude, GPT, or comparable foundation models.

Experience with prompt engineering, embeddings, semantic search, and LLM evaluation.

Experience developing REST APIs and production AI services.

Strong understanding of machine learning and deep learning concepts.

Experience with Git, CI/CD, Docker, and modern software engineering practices.

Experience deploying AI/ML solutions in cloud environments.

Strong understanding of data structures, algorithms, and distributed systems.

Preferred Qualifications

Experience with AWS and/or Azure AI/ML services.

Experience with Amazon Bedrock, Azure OpenAI, SageMaker, Azure AI Foundry, or similar platforms.

Experience with vector databases such as Pinecone, Weaviate, Milvus, OpenSearch, or pgvector.

Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable frameworks.

Experience with Kubernetes and microservices.

Experience implementing AI security, governance, observability, and guardrails.

Experience with enterprise-scale AI transformation