Senior AI/ML Engineer
2 days ago
Description :
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.
Key Responsibilities :
- Define scalable architectures for LLM integration, prompt orchestration, fine-tuning, 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.
Required Skills & Experience :
- 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.
- Familiarity with enterprise AI architecture patterns - security, scalability, monitoring, and governance.
- Strong presentation and stakeholder engagement skills.
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