Senior Al Engineer - India

Namely; Mountain View (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Namely is seeking a Senior AI Engineer in Mountain View, California, to enhance intelligent talent technology. This role involves building high-performance orchestration layers and dynamic routing engines while ensuring efficient model deployment across different regions.

The ideal candidate will have 6–8 years of experience in backend engineering, expertise in Python, and hands-on AWS experience. Join us to contribute to AI solutions that enhance workplace efficiency.

Qualifications

• 6–8 years of backend platform engineering experience.
• Expert-level Python skills.
• Hands-on experience with AWS Bedrock and hosting open-source models.

Responsibilities

• Architect and maintain high-performance orchestration layers.
• Build an advanced semantic caching layer and dynamic routing engine.
• Implement secure payload routing and telemetry dashboards.

Skills

Python

Concurrent programming patterns

AWS services

MLOps

Containerization

Education

Bachelor's or Master's in Computer Science

Tools

FastAPI

AWS Bedrock

Docker

Kubernetes

Job description

Overview

We are seeking an enthusiastic Senior AI Engineer to join our team and contribute to the development of intelligent talent technology. This is a hands‑on opportunity for those early in their career to gain experience with AI and machine learning in a real‑world, enterprise SaaS environment. You will work alongside experienced engineers and learn how large language models, recommender systems, and other AI solutions enhance the workplace.

Responsibilities

• Architect, optimize, and maintain high-performance, asynchronous orchestration layers (FastAPI) integrated with advanced inference servers (vLLM, Triton Inference Server) to host and serve open‑source models efficiently.
• Build and maintain an advanced semantic caching layer and dynamic routing engine that evaluates inbound prompts and dispatches them to the most cost‑effective or lowest‑latency model (managed services vs. self‑hosted) based on intent and token volume.
• Operationalize and maintain consistent deployments across three primary geographical regions, managing asymmetrical environment topologies (single‑region Dev environments vs. globally distributed production clusters).
• Implement enterprise‑grade rate‑limiting, secure payload routing, and advanced telemetry dashboards using Prometheus and Grafana to track token consumption, error rates, and custom system metrics for internal departmental chargebacks.

Qualifications

• Bachelor's or Master's degree in Computer Science or a related field.
• 6–8 years in backend platform engineering, systems architecture, or MLOps/LLMOps infrastructure design.
• Expert‑level Python skills with deep experience in concurrent/asynchronous programming patterns (FastAPI, Asyncio).
• Hands‑on experience with AWS Bedrock, prompt/model routing architectures, embedding generation, and hosting/serving open‑source models from Hugging Face.
• Proficiency with core AWS services (EKS, IAM, VPC), containerization (Docker, Kubernetes).