Senior Software Development Engineer AI

We are seeking an experienced AI / LLM Engineer to design, develop, and operationalize advanced language model-powered applications for enterprise use cases. This role will focus on building text-based reasoning systems, Retrieval-Augmented Generation (RAG) pipelines, and scalable prompt engineering frameworks that enhance decision-making, automation, and knowledge discovery across the organization.

As a key member of a cross-functional team, you will collaborate with business stakeholders to translate business requirements into reliable, explainable, and production-ready AI solutions. You will play a critical role in shaping enterprise AI capabilities by ensuring solutions are secure, responsible, and optimized for real-world performance.

Required Qualifications

• Strong programming experience in Python and familiarity with software engineering best practices.

• Hands-on experience building production-grade AI/ML systems, not just prototypes.

• Experience working with Large Language Models (LLMs) and APIs.

• Solid understanding of:
• Natural Language Processing (NLP) fundamentals

• Machine learning concepts (training, evaluation, overfitting, bias)

• Practical experience with:
• Retrieval-Augmented Generation (RAG) systems

• Prompt engineering and prompt optimization

• Embeddings and vector search

• Experience designing and implementing APIs, microservices, or distributed systems.

• Familiarity with model evaluation techniques and performance metrics.

• Strong debugging and problem-solving skills in complex systems.

• Experience with LLM platforms such as OpenAI, Anthropic, Google Vertex AI, or similar.

• Familiarity with orchestration frameworks like LangChain, LlamaIndex, Semantic Kernel, or equivalent.

• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, MongoDB Atlas Vector Search).

• Knowledge of MLOps practices, including CI/CD pipelines for AI systems.

• Experience deploying solutions in cloud environments (e.g., AWS, Azure, GCP).

• Exposure to agent-based architectures or multi-step AI workflows.

• Experience in financial services enterprise environments (or similar data-intensive industries).

• Experience with evaluation frameworks and benchmarking for LLMs.

• Programming: Python (primary), SQL

• LLM Platforms: OpenAI, Anthropic, Google Vertex AI

• Frameworks: LangChain, LlamaIndex, Semantic Kernel

• Vector Databases: Pinecone, Weaviate, FAISS, MongoDB Atlas Vector Search

• Data Processing: Spark, Pandas

• APIs & Services: FastAPI, Flask, REST/gRPC

• Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP)

• DevOps & MLOps: Docker, Kubernetes, CI/CD tools

• Monitoring & Evaluation: Prompt evaluation tools, logging frameworks, observability platforms