Senior Software Engineer (AI)

Design, develop, and deploy AI-powered applications by leveraging Large Language Models (LLMs), Agentic AI, and modern AI frameworks.

Build/leverage enterprise-grade AI assistants and copilots to accelerate software development, testing, documentation, customer support, and operational workflows.

Design and implement Retrieval Augmented Generation (RAG), semantic search, vector search, and enterprise knowledge solutions.

Develop AI agents and orchestrate multi-agent workflows using modern AI frameworks and Model Context Protocol (MCP).

Build scalable AI services and APIs that integrate seamlessly with enterprise applications and data platforms.

Evaluate emerging AI models, frameworks, and technologies, providing technical recommendations and proof-of-concepts.

Collaborate with cross-functional teams to identify high-value AI use cases and drive successful implementation.

Establish best practices for prompt engineering, LLM evaluation, governance, security, and responsible AI adoption.

Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related discipline.

6+ years of professional software engineering experience, including hands-on experience designing and delivering enterprise-grade AI solutions.

Proven expertise in Generative AI, LLM integration, RAG, AI Agents, cloud-native application development, and modern data platforms.

Experience with enterprise data management platforms, Databricks, Spark, AWS, and distributed systems will be a significant advantage.

Hands-on experience developing production-grade AI solutions using leading LLMs such as OpenAI, Claude, Gemini, Llama, or similar models.

Strong experience with Prompt Engineering, Retrieval Augmented Generation (RAG), AI Agents, embeddings,semantic search, and vector search.

Experience implementing enterprise AI solutions using frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, or equivalent.

Experience building AI agents using Model Context Protocol (MCP) and integrating external tools and enterprise systems.

Knowledge of AI evaluation techniques, guardrails, observability, and LLMOps best practices.

Strong programming experience in Python with proficiency in SQL, REST APIs, and either Java or .NET.

Experience developing scalable, cloud-native microservices and enterprise applications.

Strong understanding of software design principles, APIs, testing strategies, and system integration.

Experience working with enterprise data platforms such as Databricks, Snowflake, Apache Spark, Delta Lake, Apache Iceberg, and AWS.

Experience with cloud storage technologies including Amazon S3 and vector databases such as Pinecone, Chroma, Milvus, or similar.

Good understanding of modern data lakehouse architectures and enterprise data management principles.

Experience designing and optimizing ETL/ELT pipelines using technologies such as Python, SQL, Spark, Airflow, or dbt is desirable.

Experience building and operating large-scale distributed systems in cloud environments.

Experience with DevOps practices, CI/CD pipelines, Infrastructure as Code, and observability platforms.

Strong scripting and automation skills using Python, Bash, or PowerShell, with exposure to AI-assisted automation.

Experience designing scalable technical architectures and communicating complex technical concepts to both technical and non-technical stakeholders.

AWS, Databricks, Azure AI, or equivalent cloud certifications are advantageous.

Experience in Enterprise Data Management, Master Data Management (MDM), Financial Services, or Capital Markets is highly desirable.

Strong analytical and problem-solving abilities with a passion for AI-driven innovation.

Excellent communication, stakeholder management, and cross-functional collaboration skills.

Demonstrated technical leadership and the ability to mentor engineers and drive engineering best practices.

Ability to manage multiple priorities and deliver high-quality solutions in a fast-paced environment.

Curiosity, continuous learning mindset, and enthusiasm for emerging AI technologies.