We are seeking an experienced AI/ML Engineer to lead the design and implementation of AI-powered solutions leveraging large language models (LLMs), multimodal AI, and advanced generative technologies. You will play a pivotal role in defining the technical vision, architecture, and strategy for enterprise-grade GenAI systems — integrating them seamlessly into existing data, application, and cloud ecosystems.
The ideal candidate combines deep technical expertise in AI/ML with strong solution design, stakeholder management, and hands-on implementation experience.
Design and architect end-to-end Generative AI solutions (text, image, speech, code, etc.) that meet business objectives and technical requirements.
Define scalable architectures for LLM integration, prompt orchestration, retrieval-augmented generation (RAG), and multi-agent workflows.
Evaluate and select appropriate AI models, frameworks, and cloud services (e.g., OpenAI, Anthropic, Hugging Face, Azure OpenAI, Vertex AI).
Develop architecture blueprints, data flows, and API integration strategies.
Provide technical direction and mentorship to development teams on GenAI solution design and deployment best practices.
Partner with Data Scientists, ML Engineers, and MLOps teams to operationalize and monitor generative AI models.
Guide the implementation of responsible AI practices, including bias detection, data governance, and model explainability.
Stay ahead of emerging GenAI technologies, frameworks, and model capabilities.
Prototype and evaluate new approaches (e.g., RAG, fine-tuning, LoRA, function calling, multi-agent systems) to accelerate solution development.
Drive proof-of-concepts (PoCs) and pilot initiatives to demonstrate business value.
Collaborate with business leaders, product managers, and clients to identify use cases, gather requirements, and define success metrics.
Translate business challenges into AI-powered solutions with measurable outcomes.
Present architecture designs and recommendations to technical and executive audiences.
4+ years of experience in software architecture, solution design, or AI/ML systems development.
2+ years specifically in Generative AI, LLM-based solutions, or AI product architecture.
Strong hands-on experience with:
OpenAI API, LangChain, LlamaIndex, Hugging Face, or similar frameworks
Vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus)
Cloud AI platforms: Azure AI, AWS Bedrock, Google Vertex AI
Python, FastAPI, RESTful APIs, microservices, and MLOps pipelines
Deep understanding of LLM lifecycle management, prompt engineering, model evaluation, and data pipelines.
Familiarity with enterprise AI architecture patterns — security, scalability, monitoring, and governance.
Strong presentation and stakeholder engagement skills.