Machine Learning Engineer

We are seeking a highly experienced Senior Forward Deployment Engineer to lead the technical implementation, integration, and production rollout of advanced Agentic AI platforms in large-scale enterprise environments. This role combines deep engineering expertise, strong DevOps capabilities, and hands‑on ML operationalization skills to ensure seamless deployment, scalability, and reliability of AI‑driven systems.

This is a senior engineering position requiring ownership, architectural thinking, and the ability to collaborate directly with enterprise technical teams, product engineering, and leadership stakeholders.

Key Responsibilities

• Lead the end-to-end technical deployment of the Agentic AI platform across complex enterprise environments.
• Architect, design, and build integration pipelines connecting customer systems, APIs, databases, and enterprise applications.
• Deploy, operate, and scale machine learning models in production with a focus on performance, reliability, and monitoring.
• Automate end-to-end deployments using CI/CD pipelines , infrastructure-as-code , and container orchestration tools (Docker, Kubernetes).
• Ensure smooth rollout, versioning, and updates across staging, pre-prod, and production environments.

2. AI Platform Integration & Optimization

• Implement and customize platform components, SDKs, APIs, extensions, and microservices to meet customer-specific use cases.
• Build tools and automation scripts for data preprocessing , feature engineering , batch/real-time inference , and model lifecycle operations.
• Optimize model serving layers for low latency , high throughput , and efficient resource utilization .
• Improve caching, load balancing, and inference pipelines to support mission‑critical AI workloads.

3. Reliability, Security & Compliance

• Architect deployment solutions aligned with enterprise‑grade reliability, resilience, and observability standards.
• Implement best practices for security , including encryption, IAM, secret management, and network policies.
• Ensure platform deployments comply with SOC2, HIPAA, GDPR , and industry‑specific regulatory requirements.
• Set up robust monitoring, logging, and alerting frameworks for proactive issue resolution.

4. Engineering Leadership & Technical Escalation

• Act as the senior technical lead on customer deployments, owning resolution of complex engineering challenges.
• Work directly with customer engineering, infrastructure, and architecture teams to embed the platform into core production workflows.
• Provide critical field insights and feedback to the product engineering team for continuous platform improvement.
• Lead deep‑diving technical investigations, post-mortems, performance tuning, and scalability assessments.