AI engineers

You will deliver machine learning and artificial intelligence solutions to support the analytical and automation needs of the client project team. Develop, train, and implement machine learning and AI models using relevant data sources. Apply techniques such as natural language processing, computer vision, or predictive analytics as needed for project objectives. Conduct data preprocessing, feature selection, and model evaluation to ensure solution quality. Deploy AI-driven applications and monitor their ongoing performance in production environments. Document methodologies and collaborate with technical team members to align solutions with project requirements.

Hands-on AI engineers with experience building LLM-based applications, agentic workflows, RAG pipelines, prompt orchestration, text-to-SQL capabilities, evaluation frameworks, and scalable AI services. These resources should also have strong experience in model and agent evaluation, including defining evaluation criteria, creating golden datasets, measuring response quality, testing agent routing and task completion, validating groundedness, and monitoring regression across prompts, tools, and workflows.

Python, SQL, Vector DB(Qdrant, Mongo), Multi agent orchestration, Langraph, Fast API, MCP

reranking, chunking, DeepEval, Ragas, promptfoo, LangSmith evals, OpenAI Tracing, LangSmith, MLflow

Docker, CI/CD, PII handling, prompt injection testing, guardrails, audit logging, Analysis Skills, Artificial Intelligence (AI), Automation, Computer Vision, Data Modeling, Data Sets, Injections, Machine Learning, Natural Language Processing (NLP), Performance Analysis, Predictive Modeling, Production Systems, Python Programming/Scripting Language, Quality Metrics, SQL (Structured Query Language)