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Software Engineer - Gen AI Inferencing
Required Qualifications:
- 5+ years OOP in Python/Scala/Java programming experience with expert-level development skills.
- Experience with AI/ML/GenAI Lifecycle Management and Development and its ecosystem.
- Hands-on experience building frameworks using MLOps, Fine-Tuning techniques, and Inference Frameworks.
- Experience with deploying models using vLLM/Triton Inference Server in containers in production with automation.
- Performs Continuous Integration and Continuous Development (CI-CD) activities.
- Performance tuning those models and deployment to provide higher throughput.
- Track record of maintaining large-scale Python/Unix-based systems.
- Hands-on experience and knowledge of generative AI RAG processes 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 applications leveraging FastAPI services, JWT Integration, API Gateway.
- Develop efficient utilities, automation frameworks, and data science platforms that can be utilized across multiple Data Science teams for AI/ML and GenAI work.
- 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.
- Strong automation, scripting, and Python development skills. 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).
Position Summary
- This position is focused on the design, build, and operation 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 that 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, as well as design and architectural patterns.
Responsibilities:
- Codes solutions and unit tests 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 coaches the team on Continuous Integration and Continuous Development (CI-CD) practices and automating the tool stack.
- Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle.
- Performs spikes/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).
- Utilizes multiple architectural components (across data, application, business) in the design and development of client requirements.
- Manages multiple priorities and simultaneously engages with multiple teams.
- Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle.
- Is vocal and actively participates in all sessions with business stakeholders and agile teams.
- Collaborates with product teams, data analysts, and data scientists to design and build solutions.
Desired Qualifications
- Experience building & deploying Gen AI inferencing platforms with open-source toolsets, building inferencing & servicing capabilities (AI Gateway, Policy Store, Observability) for RAG/MCP use cases, etc.
- Hands-on experience driving and maintaining a culture of quality, innovation, and experimentation.
- Research on new tools and capabilities for better UI and UX for advanced analytics platforms, quick prototyping and demonstration of features and capabilities, and participation in various user forums.