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Senior Software Engineer (AI)

Gresham

Bengaluru

6+ years

1 day ago

$50.6K–65.1K/yr

Full-time

Hybrid

Skills Required LLM

RAG

Agentic AI

Gen AI

Prompt Engineering

LangChain

LlamaIndex

Hugging Face

OpenAI

Claude

Gemini

AI

Machine Learning semantic search vector search

Description Senior Software Engineer role focused on driving AI and machine learning adoption across enterprise product and engineering ecosystems. The position emphasizes enterprise-grade AI solutions, Generative AI, Agentic AI, and cloud-native technologies.

Company: Gresham

Role: Senior Software Engineer (AI)

Location: Bangalore, India

- Permanent
- Hybrid

Experience

- 6+ years of professional software engineering experience
- 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
- Hands-on experience developing production-grade AI solutions using leading LLMs such as OpenAI, Claude, Gemini, Llama, or similar models
- Solid experience with Prompt Engineering, Retrieval Augmented Generation, AI Agents, embeddings, semantic search, and vector search
- Experience implementing enterprise AI solutions using LangChain, LangGraph, LlamaIndex, Hugging Face, or equivalent
- Experience building AI agents using Model Context Protocol 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 Python, SQL, Spark, Airflow, or dbt
- 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, Financial Services, or Capital Markets is highly desirable
- Strong analytical and problem-solving abilities
- 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

Qualification

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

Responsibilities

- Lead the design, development, and deployment of enterprise-grade AI solutions
- Drive adoption of Artificial Intelligence and Machine Learning across the product and engineering ecosystem
- Enhance customer experience, improve engineering productivity, and enable intelligent data management
- Work closely with Product Managers, Architects, Data Engineers, and Software Engineers
- Help shape AI strategy for modern enterprise data platforms
- Drive innovation using Generative AI, Agentic AI, and cloud-native technologies
- Design, develop, and deploy AI-powered applications using LLMs, Agentic AI, and modern AI frameworks
- Build or leverage enterprise-grade AI assistants and copilots for development, testing, documentation, customer support, and operational workflows
- Design and implement RAG, semantic search, vector search, and enterprise knowledge solutions
- Develop AI agents and orchestrate multi-agent workflows using modern AI frameworks and MCP
- Build scalable AI services and APIs that integrate with enterprise applications and data platforms
- Evaluate emerging AI models, frameworks, and technologies and provide technical recommendations and proof-of-concepts
- Collaborate with cross-functional teams to identify high-value AI use cases and drive implementation
- Establish best practices for prompt engineering, LLM evaluation, governance, security, and responsible AI adoption

Additional Responsibilities

- The company is a global financial services technology company specialising in enterprise data automation




- Help financial institutions ensure operational, regulatory, and management data is complete, accurate, timely, and fully auditable
- Automate data controls, reconciliations, workflows, and exception management
- Enable clients to reduce operational risk, strengthen data governance, and enhance confidence in reporting
- Serve buy-side and sell-side organisations worldwide
- Support trusted, transparent, and resilient data operations in highly regulated environments
- Reasonable adjustments are provided throughout the recruitment process and employment lifecycle

Nice To Have

- Experience with enterprise data management platforms, Databricks, Spark, AWS, and distributed systems will be a significant advantage
- Experience designing and optimizing ETL/ELT pipelines using 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
- AWS, Databricks, Azure AI, or equivalent cloud certifications are advantageous
- Experience in Enterprise Data Management, Master Data Management, Financial Services, or Capital Markets is highly desirable

More Skills AI assistants, copilots, enterprise knowledge solutions, multi-agent workflows, Model Context Protocol, MCP, LLM evaluation, governance, security, responsible AI, Python, SQL, REST APIs, Java, .NET, cloud-native microservices, enterprise applications, software design, testing strategies, system integration, Databricks, Snowflake, Apache Spark, Delta Lake, Apache Iceberg, AWS, Amazon S3, vector databases, Pinecone, Chroma, Milvus, data lakehouse, enterprise data management, ETL, ELT, Airflow, dbt, distributed systems, DevOps, CI/CD, Infrastructure as Code, observability, Bash, PowerShell, AI-assisted automation, Azure AI, Master Data Management, MDM, Financial Services, Capital Markets, LangGraph, Llama

Prepare for this role

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