AI/ML Engineer

3 days ago

Multiple Locations, India BigStep Technologies Full time ₹ 2,00,00,000 - ₹ 4,00,00,000 per year

Description :

Key Responsibilities :

- 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.

Required Skills & Experience :

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 :

1. OpenAI API, LangChain, LlamaIndex, Hugging Face, or similar frameworks

2. Vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus)

3. Cloud AI platforms : Azure AI, AWS Bedrock, Google Vertex AI

4. 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

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