Who We Are
What We Do
How You’ll Contribute
Technical Ownership & Delivery
- Own end-to-end technical execution for AI/ML application initiatives, ensuring delivery against scope, quality, and timelines.
- Translate business and functional requirements into clear technical designs and actionable engineering tasks for delivery teams.
- Coordinate execution across offshore teams, AI platform teams, and stakeholders; communicate status, risks, and dependencies.
- Review offshore deliverables (code, pipelines, infrastructure changes) for quality, performance, security, and compliance.
- Fully own projects in your area, identifying gaps/opportunities and driving solutions to completion.
Hands-On Engineering (Expected)
- Actively develop, test, and deploy production features across backend services, APIs, and UI integration.
- Provide maintenance of developed software including regression testing, debugging, and root-cause analysis.
- Build tools and produce technical documentation to improve developer efficiency and alignment.
- Build and maintain test automation suites and quality gates.
AI/ML & Generative AI
- Implement and support Machine Learning and Generative AI solutions, including LLM-based systems.
- Build and support Retrieval-Augmented Generation (RAG) pipelines and vector search integrations.
- Apply prompt engineering, LLM orchestration, and agentic workflow frameworks where appropriate.
- Support model/service evaluation, monitoring, and performance tuning (quality, latency, cost).
- Ensure responsible AI practices and governance standards are followed.
Cloud, DevOps & Operations
- Operate and support AI-enabled applications in Azure and/or AWS .
- Maintain CI/CD and operational pipelines (DevOps/MLOps) to enable reliable releases.
- Own production stability during US business hours: triage incidents, coordinate fixes, and implement long-term corrective actions.
- Ensure security, reliability, and cost awareness of deployed solutions.
What You’ll Bring
Required
- 5–8 years of overall software engineering experience, including full stack application development and production support.
- Advanced proficiency in Python and strong software engineering fundamentals (design, testing, debugging).
- Hands-on experience delivering AI/ML or Generative AI solutions in production (LLM-enabled apps, RAG, orchestration).
- Experience with RAG architectures and vector databases / vector search .
- Experience with cloud platforms ( Azure and/or AWS ).
- Strong troubleshooting, incident management, and root-cause analysis skills.
- Experience working effectively with d