Job Specifications
About the job
Job Title: Java/ Gen AI Lead Consultant
Location: Austin, TX
Job type: full-time
Job Description:
We are seeking a Generative AI Lead Consultant with strong expertise in Generative AI, Agentic AI, Machine Learning, and Python. In this role, you will drive end-to-end implementation of AI solutions—from problem identification to model deployment—leveraging the latest advancements in Large Language Models (LLMs), RAG, agent frameworks, and cloud platforms.
You will work closely with client stakeholders, architects, and offshore teams to build scalable, production-grade AI systems aligned with enterprise data strategies.
Responsibilities
Lead end-to-end development of Generative AI and Agentic AI solutions, including business problem discovery, solution design, model development, optimization, and deployment.
Fine-tune, evaluate, and deploy Large Language Models and build Advanced RAG pipelines.
Architect and implement AI workflows using LangGraph, AutoGen, Crew AI, or similar agent frameworks.
Build scalable AI applications using Python, modern ML frameworks, and cloud-based GenAI services.
Deploy solutions using platforms such as AWS Bedrock, Azure OpenAI, Google Vertex AI, or IBM Watson.
Ingest and process unstructured data including PDFs, HTML, images, and audio-to-text pipelines.
Work with vector databases such as FAISS, Pinecone, Weaviate, or Azure AI Search.
Ensure data quality, data governance, and adherence to coding best practices across the AI lifecycle.
Collaborate with agile teams, drive sprint execution, provide mentorship, and coordinate with offshore delivery teams.
Build and publish reusable assets, best practices, and accelerators for AI implementations.
Required Qualifications
Bachelor’s Degree or foreign equivalent (or 3 years of relevant progressive experience per year of missing education).
7+ years of experience in Information Technology.
4+ years of hands-on experience in Generative AI / Agentic AI / Machine Learning / Data Science.
Strong proficiency in Python programming.
Experience deploying AI applications using agent frameworks such as LangGraph, AutoGen, or Crew AI.
Experience with cloud-native Gen AI services on AWS, Azure, GCP, or IBM Watson.
Hands-on experience with RAG, multiple LLMs, and GenAI pipelines.
Experience processing unstructured data (PDF, image, HTML, OCR, audio-to-text).
Strong understanding of data gathering, data quality, system architecture, and ML coding best practices.
Experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search).
Experience with Agile/Lean development methodologies.
Preferred Qualifications
Experience with multiple programming languages—Python, R, Scala, Java, SQL.
Hands-on experience with CI/CD pipelines & DevOps tools (Jenkins, GitHub Actions, Terraform).
Proficiency with both SQL and NoSQL databases (PostgreSQL, MongoDB, CosmosDB, DynamoDB).
Deep Learning experience: CNNs, RNNs, LSTMs, and exposure to emerging research.
Experience with AI/ML frameworks such as TensorFlow, PyTorch, LangChain.
Strong background in LLM fine-tuning, optimization, quantization, and local deployment.
Experience building RESTful APIs using FastAPI, Flask, or Django.
Knowledge of model evaluation tools such as DeepEval, FMEval, RAGAS, Bedrock evaluations.
Experience with computer vision, time-series, and NLP pipelines.
Strong Big Data skills: HDFS, Hive, Spark, Scala.
Exposure to data visualization tools (Tableau) and data query tools (SQL, Hive).
Strong applied statistics background (distributions, statistical testing, regression, etc.).