AI Development Platform Engineer

We are seeking a skilled and innovative AI Development Platform Engineer to join our advanced technology team.

In this role, you will drive the design, development, and deployment of scalable, secure, and high-performing AI/ML platforms—focusing especially on Generative AI.

You will play a critical role in building tools and services that enable teams to leverage large language models (LLMs), vector databases, container orchestration, and cloud-native capabilities.

Key Responsibilities:

• Develop reusable tooling and self-service platforms for deploying enterprise AI solutions.
• Build common frameworks to support scalable deployment of GenAI use cases using pre-trained and fine-tuned models.
• Collaborate across development teams to enhance platform services, developer experience, and AI readiness.
• Utilize Kubernetes/OpenShift for building and orchestrating containerized workloads.
• Implement GitOps-based deployment strategies with tools like Helm, Kustomize, and JFrog Artifactory.
• Integrate with vector databases for embeddings and retrieval-augmented generation (RAG).
• Lead platform-level decisions including service auth, state management, observability, and reliability.
• Drive adoption of AI agent frameworks (Langchain, LangGraph) and orchestration techniques.
• Maintain observability across systems using OpenTelemetry tools (Grafana, Loki, Prometheus, Cortex).
• Participate actively in Agile/Scrum ceremonies, helping foster a DevOps-first, collaborative culture.

Required Qualifications:

• 5+ years of experience in software engineering with strong application development expertise.
• Proficient in Python (Flask/FastAPI) or equivalent languages.
• Strong experience with RESTful service design, API Gateways, and scalable microservice architecture.
• Expertise in Kubernetes (preferably OpenShift), container packaging, and deployment automation.
• Hands‑on experience with DevOps & GitOps practices (CI/CD pipelines, Jenkins, ArgoCD, etc.).
• Familiar with data platforms: SQL/NoSQL databases, Kafka, Redis.
• Proficient in OAuth2.0, security standards, and secure software development lifecycle.
• Experience in multiprocessing, multithreading, async I/O, and performance tuning.
• Understanding of Machine Learning/Deep Learning, with knowledge of frameworks like TensorFlow or PyTorch.
• Knowledge of cloud‑native design, observability practices, and site reliability engineering principles.
• Strong written and verbal communication with a collaborative, mentoring approach.

Preferred Qualifications:

• Hands‑on experience with Generative AI, LLMs (GPT, LLaMA, HuggingFace), and model fine‑tuning.
• Experience building AI agents, implementing Agentic Orchestration and Multi‑Agent Workflows.
• Familiar with frameworks like Langchain, LangGraph, and modern vector store technologies.
• Understanding of ModelOps/LLMOps/MLOps pipelines.
• Experience deploying apps in public and private cloud environments with Blue/Green or Canary strategies.
• Proficient in managing stateful and stateless architectures and event‑driven systems.

Educational Requirements:

Bachelor's or Master’s degree in Computer Science, AI/ML, or related field, or equivalent professional experience.