Job Summary :

We are seeking an experienced Senior AI Developer to lead the design and implementation of advanced AI-powered applications and enterprise-grade Generative AI solutions. The ideal candidate will bring strong expertise in Python, machine learning, LLMs, RAG architectures, and AI application development.

Key Responsibilities :

- Architect, develop, and deploy scalable AI/ML applications for complex business use cases.

- Lead the development and integration of Generative AI solutions using LLMs and foundation models.

- Design and implement advanced RAG pipelines, semantic search systems, and knowledge retrieval solutions.

- Develop AI agents, tool-calling workflows, and multi-agent systems.

- Evaluate and integrate LLMs from providers such as OpenAI, Azure OpenAI, Anthropic, and open-source model ecosystems.

- Optimize model performance, inference latency, token consumption, and application costs.

- Design robust APIs and microservices to integrate AI capabilities into enterprise applications.

- Establish standards for AI application architecture, testing, observability, security, and deployment.

- Implement model evaluation frameworks, quality metrics, and safeguards to improve AI reliability.

- Collaborate with product managers, architects, data scientists, and engineering teams to define technical solutions.

- Mentor developers, conduct code reviews, and promote engineering best practices.

- Support production deployments, troubleshooting, monitoring, and continuous improvement of AI systems.

Tech Stack & Requirements :

- 8-10 years of experience in software engineering, AI/ML development, or related technical roles.

- Strong expertise in Python and software engineering principles.

- Hands-on experience developing and deploying production-grade AI/ML applications.

- Deep understanding of Generative AI, LLMs, prompt engineering, and model integration.

- Strong experience designing RAG architectures, embedding pipelines, vector search, and retrieval optimization.

- Experience with frameworks such as LangChain, LlamaIndex, or equivalent tools.

- Experience integrating commercial and open-source LLMs through APIs or inference frameworks.

- Strong understanding of REST APIs, microservices, distributed systems, and application architecture.

- Experience with Docker, Kubernetes, CI/CD, and cloud platforms such as AWS, Azure, or GCP.

- Knowledge of AI evaluation, monitoring, guardrails, data privacy, and application security.

Preferred Skills :

- Experience with AI agents, multi-agent orchestration, and tool-calling architectures.

- Exposure to fine-tuning, model adaptation, quantization, or inference optimization.

- Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.

- Familiarity with MLOps, LLMOps, model lifecycle management, and AI observability.

- Experience with enterprise AI governance and responsible AI practices.

Education : Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field.