Generative AI Engineer

Altimetrik delivers outcomes for our clients by rapidly enabling digital business & culture and infuse speed and agility into enterprise technology and connected solutions. We are practitioners of end-to-end business and technology transformation. We tap into an organization’s technology, people, and assets to fuel fast, meaningful results for global enterprise customers across financial services, payments, retail, automotive, healthcare, manufacturing, and other industries. Founded in 2012 and with offices across the globe, Altimetrik makes industries, leaders and Fortune 500 companies more agile, empowered and successful.

Altimetrik helps get companies get “unstuck”. We’re a technology company that lives organizations a process and context to solve problems in unconventional ways. We’re a catalyst for organization’s talent and technology, helping teams push boundaries and challenge traditional approaches. We make delivery more bold, efficient, collaborative and even more enjoyable.

JD:

GenAI Engineer

• 8-10 years of relevant experience in Apps Development or systems analysis role
• Core AI/ML Foundations:
• Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs).
• Generative AI & LLM Expertise:
• Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs.
• Critical: Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation.
• Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc.
• Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates.
• Hands-on experience with agentic framework-based use case implementation.
• Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features.
• Programming & Data Engineering:
• Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex.
• Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools.
• Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval.
• Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing.
• Deployment & MLOps:
• Critical: Hands-on experience deploying GenAI-based models to production environments.
• Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines.
• Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments.
• Cloud & Containerization:
• Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment.
• Soft Skills:
• Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problems.