Customer Implementation Engineer ( Python | AI/ML)

Ovii's Interpretation of the Role

The Implementation Engineer builds and deploys Python‑based backend services that integrate AI/ML models into enterprise workflows. You will partner with Customer Success, ML, and Backend teams to deliver reliable, scalable solutions for large‑scale clients.

Role Snapshot

• Python backend development
• AI/ML integration
• Enterprise system integrations
• Cloud deployment (Azure/AWS/GCP)
• Customer‑facing delivery
• Mentoring junior engineers

Must-Have Requirements

• Python
• backend fundamentals
• microservices
• APIs
• FastAPI / Flask / Django
• RESTful architecture
• PostgreSQL / MongoDB
• Azure / AWS / GCP
• problem‑solving
• communication
• Python development
• API design

Nice-to-Have Signals

• AI/ML pipeline experience
• LLM / RAG implementation
• Java
• NLP / text processing
• Docker
• Kubernetes
• Kafka / RabbitMQ
• CI/CD tools
• startup experience
• open‑source contributions
• technical writing
• AI/ML pipeline work
• LLM / RAG applications

Work Setup

• Location: Bengaluru, India
• Work mode: HYBRID
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement
• Certifications
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Develop and maintain Python services, APIs, and integration layers for customer implementations
• Build data ingestion, transformation, and validation pipelines that feed AI/ML workflows
• Integrate LLM, retrieval‑augmented generation, and other NLP components into client environments
• Configure, deploy, and monitor services on Azure, AWS, or GCP ensuring reliability and observability
• Collaborate with Customer Success and Solutions teams to translate business requirements into technical specifications
• Own end‑to‑end technical delivery for enterprise accounts, managing scope, sequencing, and blockers
• Provide architectural guidance, best‑practice recommendations, and scalable patterns
• Participate in code reviews, maintain coding standards, and document implementation playbooks
• Mentor junior engineers and contribute to internal tooling and automation

Good Fit If You Have

• Experience with AI/ML or NLP pipelines (LLM, RAG) is a plus
• Prior startup or fast‑growth environment experience appreciated
• Open‑source contributions or technical writing background is beneficial