Associate Consultant, Generative AI

48 Wall Street,10005 New York, United States We are growing our Generative AI consulting practice and looking for motivated recent graduates to join as GenAI Consultants. You'll work at the intersection of cutting‑edge AI and real business problems — helping clients across industries design, build, and deploy LLM‑powered solutions that create tangible value. This is a hands‑on technical role. You'll contribute to the full lifecycle of GenAI projects: from architecture and prototyping through to production deployment, evaluation, and iteration. We invest heavily in your development, and expect you to do the same. What You’ll Do You’ll design and implement GenAI/LLM solutions leveraging models such as Claude, GPT, Gemini, Llama, and Mistral — selecting the right approach (RAG, agents, fine‑tuning, prompt engineering) for each client context. You’ll support senior architects in designing scalable, secure, and compliant AI applications while building hands‑on experience across the full stack. Responsibilities LLM/GenAI System Development: Design, build, train, fine‑tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT‑x, Claude, Gemini, Llama, Mistral) and other generative techniques. Assist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications. Application Development: Develop applications powered by GenAI models (both self‑managed and API‑accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.). Advanced Prompt Engineering: Design and optimize effective prompts (e.g., few‑shot, Chain/Tree/Graph of Thought, ReAct, Self‑reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions. RAG Implementation: Design and implement Retrieval‑Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre‑determined knowledge sources, providing traceability (source attribution). Model Selection & Fine‑Tuning: Select and fine‑tune appropriate models (including multimodal – VLM, SLM – Visual Language Models, Small Language Models) to create higher‑quality content (text, image, audio, code, etc.) and maximize business value creation opportunities. Integration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP). Evaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end‑to‑end security and compliance processes. Research & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing. Collaboration: Work effectively within cross‑functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non‑technical). Documentation: Document processes, methodologies, and best practices for knowledge sharing and future reference. Use Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis). Qualifications Bachelor’s Degree Required Recent graduate (within 2 years) in CS, Engineering, Data Science, or equivalent Familiarity with at least one GenAI framework (LangChain, LlamaIndex, or similar) Foundational knowledge of NLP concepts, vector embeddings, and semantic search Exposure to cloud platforms (AWS, Azure, or GCP) Ability to explain technical concepts clearly to diverse audiences All candidates must hold — or demonstrate the clear ability to obtain within one week of hire — the Claude Certified Architect – Foundations (CCA‑F) certification from Anthropic. Preferred Qualifications Master’s Degree Preferred Prior experience building agentic AI systems (LangGraph, AutoGen, etc.) Familiarity with vector databases (Pinecone, Chroma, pgvector, OpenSearch) Experience with or understanding of the Model Context Protocol (MCP) Hands‑on fine‑tuning experience with open‑source LLMs Familiarity with Docker, Git, and CI/CD workflows Additional Information Competitive Compensation Annual Base Salary Range: $80,000‑110,000 annually, commensurate with experience and qualifications Annual performance‑based discretionary bonus Robust Health Coverage 3 Medical plans Dental and Vision Life, AD&D and other voluntary insurance Tax‑Advantaged Accounts 4% matching and 100% vested upon enrollment Health Savings Account (HSA) Flexible Spending Account (FSA) Health, Dependent Care, Commuter Family Friendly Benefits 100% paid parental leave for all new parents with eligible tenure Building Healthy Families program if enrolled through Medical plan Time Off to Recharge Generous Paid Time Off (PTO) policy Extras that Make Life Easier College savings and student loan repayment assistance Monthly cell phone stipend Access to wellness programs at no cost if enrolled through Medical plan, including: Employee Assistance Program at no cost Diversity, Equity, Inclusion & Belonging At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. #J-18808-Ljbffr Sia Partners'