AI Expert

Title: AI Expert Location: Hartford, CT (Hybrid - Onsite Tuesday through Thursday; Remote Monday and Friday) Duration: 6+ months Implementation Partner: Infosys End Client: To be disclosed JD We are seeking a highly skilled AI Evangelist / AI Expert to drive AI-led transformation across the account, shape the AI strategy, and enable scalable adoption of Generative AI, Machine Learning, and full-stack AI engineering capabilities. This role will partner with client stakeholders, engineering teams, and leadership to identify high-value opportunities, define solution architectures, build PoCs/POVs, and guide implementation using modern AI frameworks, model-tuning techniques, and orchestration patterns. Key Responsibilities Strategic AI Leadership & Evangelization Act as the primary AI thought leader for the account, driving awareness, education, and advocacy for emerging AI/GenAI capabilities. Partner with business and technology leaders to shape the AI roadmap, influence strategy, and embed AI in transformation initiatives. Conduct AI workshops, ideation sessions, and executive briefings to help define and prioritize high-impact use cases. AI Solution Architecture & Full-Stack AI Engineering Lead design and development of end-to-end AI/GenAI solutions, including data ingestion, model orchestration, inference services, and integration with enterprise systems. Architect multi-model pipelines using platforms and frameworks such as LangChain, LangGraph, Pydantic, vector databases, LLM frameworks, and cloud-native services. Build scalable, secure, and modular AI components for repeatability across use cases. Model Development, Tuning & Optimization Apply advanced model-tuning techniques such as PEFT, LoRA, QLoRA, SFT, and Retrieval-Augmented Generation (RAG). Evaluate, fine-tune, and optimize foundation models (open-source and enterprise) for domain-specific workloads. Perform model benchmarking, guardrail design, prompt engineering, evaluation, and continuous improvement. GenAI & ML Engineering Excellence Build prototype agents, copilots, AI automation flows, and domain-context solutions using modern AI frameworks. Develop ML pipelines, feature engineering workflows, evaluation metrics, and monitoring dashboards. Ensure adherence to responsible AI, security, compliance, and governance standards. Client Engagement & Value Realization Lead client discussions, articulate solution approaches, and build strong trust across business and technology stakeholders. Drive use case discovery, feasibility assessment, and ROI analysis to prioritize AI initiatives. Own delivery of PoCs/POVs ensuring measurable business outcomes and technical excellence. Collaboration & Enablement Mentor internal teams, conduct training, build reusable accelerators, and foster an AI-first engineering culture. Collaborate with multi-disciplinary teams data engineering, cloud, architecture, and domain SMEs to deliver integrated solutions. Required Skills & Experience Core AI & GenAI Expertise Deep experience with Generative AI, LLMs, multi-modal models, RAG systems, and agent-based architectures. Strong knowledge of ML algorithms, NLP/NLU techniques, transformers, embeddings, and evaluation frameworks. Model Tuning & Optimization Hands-on expertise with PEFT, LoRA, QLoRA, parameter-efficient fine-tuning, and prompt-tuning strategies. Experience customizing open-source and enterprise LLMs for domain-specific tasks. Frameworks, Tools & Libraries. Proficiency in: LangChain, LangGraph, Pydantic FAISS / Chroma / Milvus or other vector DBs PyTorch / TensorFlow HuggingFace ecosystem OpenAI / Azure OpenAI / Claude / Gemini APIs Full-Stack AI Engineering Strong Python engineering skills for building orchestration, pipelines, and backend services. Experience deploying AI workloads on Azure/AWS/GCP (or equivalents). Understanding of MLOps / AIOps, CI/CD pipelines, containerization, and microservices Consultative & Evangelization Skills Exceptional communication and storytelling abilities. Strong client-facing experience-handling CxO conversations, workshops, roadmap presentations. Ability to simplify complex AI concepts for business and technical audiences. Preferred Qualifications 8-15+ years of experience in AI/ML, with at least 3-5 years in GenAI/LLM-based solutions. Master's degree or specialization in Computer Science, AI, ML, Data Science, or related fields. Certifications in cloud AI services (Azure AI, AWS ML, GCP Vertex AI) are highly desirable.

Created: 2026-03-04