Software Engineer - AI/RAG

Software Engineer - AI/RAG

Position Summary

This position is focused on design, build, and operate of reusable toolkits for Gen AI RAG capabilities.

This job is responsible for developing and delivering complex requirements to accomplish business goals. Key responsibilities of the job include ensuring that software is developed to meet functional, non-functional and compliance requirements, and solutions are well designed with maintainability/ease of integration and testing built-in from the outset. Job expectations include a strong knowledge of development and testing practices common to the industry and design and architectural patterns.

Responsibilities:

• Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
• Designs, develops, and modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained
• Mentors other software engineers and coach team on Continuous Integration and Continuous Development (CI-CD) practices and automating tool stack
• Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle
• Performs spike/proof of concept as necessary to mitigate risk or implement new ideas
• Automates manual release activities
• Designs, develops, and maintains automated test suites (integration, regression, performance)
• Performs Continuous Integration and Continuous Development (CI-CD) activities.
• Contributes to story refinement and definition of requirements.
• Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle.
• Manage multiple priorities, and simultaneously engage with multiple teams.
• Be vocal and actively participate in all session with business stakeholders and agile teams.
• Collaborate with product teams, data analysts and data scientists to design and build solutions.
• Utilizes multiple architectural components (across data, application, business) in design and development of client requirements.

Required qualifications:

• 5 years of relevant experience required.
• Experience in Semantic Search, data processing ,Data & Analytics, Data pipeline.
• Experience in OOP in Python/Scala/Java programming experience with expert level development skills.
• Hands on experience and knowledge generative AI RAG process for various use cases, including chunking, embedding, retrieval, reranking and summarization.
• Hands-on experience in application development in one or more areas MongoDB, Redis, Angular/React Frameworks, Containerization, Building API based application leveraging FAST API services, JWT Integration, API Gateway
• Develop efficient utilities, automation frameworks, data science platforms that can be utilized across multiple Data Science teams for AI/ML and GenAI work.
• Experience with AI/ML/GenAI Lifecycle Management and Development and its Ecosystem. Hands on experience building frameworks using MLOps, Fine Tuning techniques, Inference Frameworks
• Building API based application leveraging FAST API services, JWT Integration, API Gateway
• Working in large sized teams that collaboratively develop on a shared multi-repo codebase using IDEs (e.g. VS Code rather than Jupyter Notebooks), Continuous Integration (CI), Continuous Deployment (CD) and Continuous Testing
• Hands-on DevOps experience with one or more of the following enterprise development tools: Version Control (GIT/Bitbucket), Build Orchestration (Jenkins), Code Quality (SonarQube and pytest Unit Testing), Artifact Management (Artifactory) and Deployment (Ansible)

Desired Qualifications

• Experience developing Gen AI training and RAG platform with open-source model, inferencing & servicing capabilities, MCP modules etc..

Skills:

• Application Development
• Automation
• Influence
• Solution Design
• Technical Strategy Development
• Architecture
• Business Acumen
• DevOps Practices
• Result Orientation
• Solution Delivery Process
• Analytical Thinking
• Collaboration
• Data Management
• Risk Management
• Test Engineering