Job Title: Generative AI (GenAI) Architect
Location: Remote
Duration: 6-12+Months contract
As a Lead Technical Consultant, you will participate in all aspects of the software development lifecycle which includes estimating, technical design, implementation, documentation, testing, deployment and support of application developed for our clients. As a member working in a team environment, you will work with solution architects and developers on interpretation/translation of wireframes and creative designs into functional requirements, and subsequently into technical design.
As a Generative AI Architect, you will have hands-on experience architecting and implementing retrieval-augmented generation (RAG) pipelines, agentic multi-agent workflows and vector database integrations (e.g. Pinecone, Weaviate), leveraging GenAI frameworks such as LangChain/Autogen, LangGraph and Haystack on AWS, Azure OpenAI, and Google Cloud AI. The ideal candidate will have a strong background in fine-tuning and deploying large language models, designing custom prompt-engineering strategies, and building end-to-end GenAI applications. The candidate also will have the ability to propose, direct and implement custom solutions based on different usecases.
Responsibilities for Internal Candidates
* Design, develop, and deploy GenAI solutions—including RAG systems and agentic orchestration—by integrating vector stores and cloud AI services (AWS SageMaker/Bedrock, Azure OpenAI, GCP Vertex AI).
* Implement and optimize transformer-based models (LLMs) for advanced NLP use cases, such as dynamic document retrieval, summarization, question answering and conversational agents.
* Collaborate with cross-functional teams to integrate GenAI services (APIs, microservices) into enterprise applications and automate workflows for content generation and analysis.
* Develop end-to-end automation pipelines using GenAI orchestration frameworks (LangChain, Autogen, Haystack) and manage vector embeddings, metadata stores, and retrieval layers.
* Monitor retrieval performance, model quality (accuracy, latency, hallucination rates) and user feedback loops to continuously refine prompt templates, embedding configurations, and agent policies.
* Stay updated with the latest advancements in GenAI architectures, vector database innovations, multi-agent strategies, and emerging frameworks like LangGraph and Autogen.
* When required, design and develop deterministic python code to augment LLM based solutions, based on usecases
Qualifications for Internal Candidates
* Passionate about advanced GenAI capabilities, including RAG, vector similarity search, and agentic system design.
* 5+ years of AI/ML development experience, with at least 2 years focused on building and deploying GenAI solutions.
* Proficiency deploying and orchestrating LLM-based pipelines on cloud AI platforms (AWS SageMaker/Bedrock, Azure OpenAI, Google Vertex AI) and managing associated infrastructure.
* Strong knowledge of core ML frameworks (TensorFlow, PyTorch) and GenAI-specific toolkits (Hugging Face Transformers, OpenAI API, LangChain, Autogen, Haystack).
* Experience developing and implementing python APIs or functions
* Proven experience building retrieval-augmented generation systems, fine-tuning LLMs for domain adaptation, and implementing prompt-engineering best practices.
* Excellent problem-solving skills and ability to work in an agile development environment.
* Strong communication skills to collaborate with technical and non-technical teams.
Preferred Qualifications:
* Experience designing agentic multi-agent GenAI workflows using frameworks like LangGraph and applying reinforcement learning for LLM-driven decision making.
* Experience developing GenAI applications for automated document ingestion, processing, summarization, or enterprise email routing.
* Familiarity with API development, microservices architecture, and containerization (Docker, Kubernetes).
Thanks,
Srikanth Donkani
Lead-Talent Acquisition
(W) 312-448-6138
22260 Haggerty Road, Suite#285, Northville, MI 48167.
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