AI / LLM Engineer

Job Title: AI / LLM Engineer

Experience Level: 23 Years

Employment Type: Full-Time

Location: Indore

Position Summary

We are seeking an AI / LLMOps Engineer with 23 years of hands-on software development, DevOps, and cloud experience to build and scale our Generative AI infrastructure. In this role, you will bridge the gap between AI development and operations by building reliable Python microservices, managing automated CI/CD pipelines, and deploying Large Language Model (LLM) applications across cloud environments (AWS, Azure, or GCP).

Key Responsibilities

AI Application Development: Build, maintain, and optimize Python-based back-end services, microservices, and REST APIs (using FastAPI or Flask) to integrate LLM features and orchestration frameworks (LangChain, LlamaIndex).

LLMOps & Deployment: Operationalize LLM pipelines, RAG systems, and vector databases in production environments while managing prompt versions, evaluation suites, and cost/latency tracking.

Cloud & Infrastructure as Code: Provision and scale cloud resources across AWS, GCP, or Azure using IaC tools like Terraform or CloudFormation.

CI/CD & Automation: Design, build, and maintain automated continuous integration and continuous deployment (CI/CD) pipelines (GitHub Actions, GitLab CI, Jenkins) for both code and AI model releases.

Containerization & Orchestration: Package applications with Docker and assist in managing containerized workloads using Kubernetes or cloud container services (AWS ECS, GCP Cloud Run, Azure AKS).

Observability & Monitoring: Implement logging, metrics, and tracing for standard infrastructure and LLM workflows (using tools like Grafana, Datadog, Prometheus, LangSmith, or Langfuse).

Required Qualifications & Skills

Experience: 23 years of commercial software engineering experience with a strong focus on Python, cloud computing, and DevOps practices.

Programming & Frameworks: Proficiency in Python and experience with API frameworks (FastAPI/Flask) and LLM tools (LangChain, LlamaIndex, OpenAI/Anthropic APIs).

Cloud Knowledge: Practical experience with at least one major cloud provider (AWS, GCP, or Azure) and core services.

DevOps & Containers: Hands-on experience with Docker, version control (Git), CI/CD execution, and basic Infrastructure as Code (Terraform).

AI Knowledge: Solid understanding of Generative AI concepts, prompt engineering, vector databases (Pinecone, FAISS, Weaviate), and RAG architectures.

Preferred Qualifications

Cloud certifications (e.g., AWS Certified Developer / Solutions Architect, Azure AI Engineer, GCP Cloud Engineer).

Basic experience managing Kubernetes clusters or Helm charts.

Familiarity with fine-tuning open-source LLMs (vLLM, Ollama) or optimizing token/API consumption costs.

Compensation: 20,000.00 - 50,000.00 per month

Work Location: In person .