Job Description
We are seeking a skilled and innovative AI Development Platform Engineer to join our Advanced Technology team. In this role, you will lead the design and deployment of scalable, secure, and high-performance AI/ML infrastructure with a focus on Generative AI (GenAI). This is a strategic, hands-on engineering position that will empower internal teams to leverage Large Language Models (LLMs), vector databases, and cloud-native platforms with speed and confidence.
Key Responsibilities
- Architect and develop reusable tooling and self-service platforms to streamline enterprise AI solution deployment.
- Build scalable frameworks supporting Generative AI use cases using pre-trained and fine-tuned LLMs.
- Collaborate with developers, ML engineers, and DevOps teams to enhance platform services, developer experience, and operational excellence.
- Use Kubernetes / OpenShift to manage and orchestrate containerized AI workloads.
- Implement GitOps deployment strategies using tools like Helm, Kustomize, ArgoCD, and JFrog Artifactory.
- Integrate and manage vector databases for embedding-based search and Retrieval-Augmented Generation (RAG) patterns.
- Make platform-level architectural decisions covering authentication, state management, observability, and reliability.
- Advocate for and manage AI agent frameworks such as Langchain and LangGraph.
- Maintain comprehensive observability with tools like Grafana, Prometheus, Loki, and OpenTelemetry.
- Engage in Agile ceremonies and promote a DevOps-first collaborative engineering culture.
Required Qualifications
- 5+ years of hands-on software engineering experience, especially in backend or platform development.
- Proficient in Python (e.g., Flask, FastAPI) or equivalent.
- Deep understanding of RESTful APIs, microservices architecture, and scalable system design.
- Expertise in Kubernetes/OpenShift and container orchestration.
- Strong background in CI/CD, DevOps, and GitOps with tools like Jenkins, ArgoCD, and Terraform.
- Familiar with SQL/NoSQL, Kafka, Redis, and event-driven architectures.
- Experience with OAuth 2.0, secure development, and compliance.
- Knowledge of multiprocessing, multithreading, async I/O, and performance tuning.
- Understanding of ML/DL concepts, familiar with TensorFlow or PyTorch.
- Exposure to cloud-native design, SRE principles, and observability.
Preferred Qualifications
- Hands-on experience with Generative AI and LLMs like GPT, LLaMA, Hugging Face.
- Experience with AI agents, Agentic Orchestration, and Multi-Agent Workflows.
- Familiar with Langchain, LangGraph, and vector database tech such as Pinecone, FAISS, Weaviate.
- Knowledge of ModelOps/LLMOps/MLOps pipelines.
- Experience deploying in hybrid/multi-cloud environments with Blue/Green or Canary strategies.
- Ability to build both stateful and stateless systems.
Educational Requirements
- Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, or similar, or equivalent professional experience.