AI Engineer
- Posted a month ago
- Be among the first 10 applicants
Job Description
Roles And Responsibilities
[Confidential Information]
- AI Engagements: Independently manage end-to-end delivery of AI-led transformation projects across industries, ensuring value realization and high client satisfaction.
- Strategic Consulting & Roadmapping: Identify key enterprise challenges and translate them into AI solution opportunities, crafting transformation roadmaps that leverage RAG, LLMs, and intelligent agent frameworks.
- LLM/RAG Solution Design & Implementation: Architect and deliver cutting-edge AI systems using Python, LangChain, LlamaIndex, OpenAI function calling, semantic search, and vector store integrations (FAISS, Qdrant, Pinecone, ChromaDB).
- Agentic Systems: Design and deploy multi-step agent workflows using frameworks like CrewAI, LangGraph, AutoGen or ReAct, optimizing tool-augmented reasoning pipelines.
- Client Engagement & Advisory: Build lasting client relationships as a trusted AI advisor, delivering technical insight and strategic direction on generative AI initiatives.
- Hands-on Prototyping: Rapidly prototype PoCs using Python and modern ML/LLM stacks to demonstrate feasibility and business impact.
- Thought Leadership: Conduct market research, stay updated with the latest in GenAI and RAG/Agentic systems, and contribute to whitepapers, blogs, and new offerings.
- Leadership Quality: Proven track record in leading cross-functional teams and delivering enterprise-grade AI projects with tangible business impact.
- Business Consulting Mindset: Strong problem-solving, stakeholder communication, and business analysis skills to bridge technical and business domains.
- Python & AI Proficiency: Advanced proficiency in Python and popular AI/ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, spaCy, NLTK). Solid understanding of NLP, embeddings, semantic search, and transformer models.
- LLM Ecosystem Fluency: Experience with OpenAI, Cohere, Hugging Face models; prompt engineering; tool/function calling; and structured task orchestration.
- Independent Contributor: Ability to own initiatives end-to-end, take decisions independently, and operate in fast-paced environments.
- Education: Bachelor's or Master's in Computer Science, AI, Engineering, or related field.
- Experience: Minimum 5 years of experience in consulting or technology roles, with at least 3 years focused on AI & ML solutions.
- Cloud Platform Expertise: Strong familiarity with Microsoft Azure (preferred), AWS, or GCP — including compute instances, storage, managed services, and serverless/cloud-native deployment models.
- Programming Paradigms: Hands-on experience with both functional and object-oriented programming in AI system design.
- Hugging Face Ecosystem: Proficiency in using Hugging Face Transformers, Datasets, and Model Hub.
- Vector Store Experience: Hands-on experience with FAISS, Qdrant, Pinecone, ChromaDB.
- LangChain Expertise: Strong proficiency in LangChain for agentic task orchestration and RAG pipelines.
- MLOps & Deployment: CI/CD for ML pipelines, MLOps tools (MLflow, Azure ML), containerization (Docker/Kubernetes).
- Cloud & Service Architecture: Knowledge of microservices, scaling strategies, inter-service communication.
- Programming Languages: Proficiency in Python and C# for enterprise-grade AI solution development.
- Excellent customer interfacing and stakeholder engagement skills.
- Strong verbal and written communication in business and technical contexts.
- High attention to detail and structured problem-solving.
- Passion for AI ethics, safety, performance, and optimization in enterprise-grade systems.
[Confidential Information]
More Info
Key Skills
scikit-learn
OpenAI function calling
Qdrant
Hugging Face
MLflow
Pinecone
LangGraph
ChromaDB
Cohere
LangChain
CrewAI
vector store integrations
AutoGen
spaCy
FAISS
OpenAI
LlamaIndex
About Company
Skills:
Java Microservices, Git, Docker, Kubernetes, LangChain, RAG systems, Crew.ai, cloud-native architecture, vector databases, embedding models, knowledge retrieval systems, prompt engineering, Autogen, LLM optimization techniques, RAG pipelines, async programming, advanced Python programming
Skills:
containerization , Sparql, Rdf, Docker, Python, Oauth2, Azure, SHACL, Lang Chain, Lang Graph, Security, CI CD, Agentic frameworks, LLM orchestration, Evaluation, IEC 61850, Cloud and infra-Azure, COMTRADE, Vector databases, Production-grade async clean APIs, Knowledge graphs, RAG, Local LLM inference, OIDC
Skills:
.NET, Github, Paas, Nodejs, ADO, Angular, Tensorflow, Nosql, React, Pytorch, Sonarqube, Python, AWS, Java, Sql, DevSecOps, AWS Bedrock, micro-services, SRE, LangFuse, MLflow, Azure OpenAI, LangSmith, FaaS, LangGraph, Vertex AI, LangChain, Lean, FinOps, infrastructure-as-code, unit testing frameworks, Xp
Skills:
Microsoft Azure, Python, GitHub Copilot, RESTful API design, AI ethics and regulations
Skills:
quantitative analytics , Typescript, Javascript, Docker, Python, AWS, Java, Version Control, Devops, Git, Gcp, DevSecOps, Azure, Kubernetes, Data Interpretation, IDES, Go, Cloud environments, SDLC understanding, MCP Infrastructure requirements, AI-first engineering practices, LLMs, infrastructure-as-code, observability platforms