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AMS Accelerate IT
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We are seeking a talented Backend Software Engineer with a focus on AI/ML to join our team. In this role, you will be responsible for designing, implementing, and maintaining scalable backend services primarily in Python. Your main tasks will involve building and managing data pipelines for AI/ML applications, as well as operationalizing and deploying Generative AI systems for production use.
Design, implement, and maintain scalable backend services in Python
Build and maintain data pipelines for AI/ML applications for production use-cases
Operationalize and deploy Generative AI systems (APIs, SDKs, pipelines)
Develop APIs to serve AI features to downstream applications
Orchestrate agentic workflows using frameworks like LangChain, LangGraph, or custom solutions
Ensure monitoring, logging, and observability of GenAI services
Collaborate cross-functionally to ensure system performance, scalability, and reliability
This position is ideal for a hands-on software engineer with significant exposure to AI product development, rather than a data science or AI/ML research role.
We are looking for individuals who excel in operational excellence, have deployment experience, and possess systems-level thinking for real AI applications.
5+ years of practical experience as a Python backend developer
Strong knowledge of software engineering principles, clean code practices, and testing methodologies
Practical experience with Python backend frameworks: FastAPI (preferred), Flask or Django
Practical experience with SQL databases and related Python libraries
Hands-on experience with cloud platforms: Azure (preferred), AWS or GCP
Experience designing and implementing scalable backend services (APIs, data pipelines, SDKs, etc.)
Practical experience with building and deploying AI-based applications, including LLMs and embedding models (e.g., OpenAI, Anthropic, Hugging Face)
Familiarity with Retrieval-Augmented Generation (RAG) based systems, agentic workflows and Generative AI applications
Familiarity with containerized development with Docker
Experience with data science Python libraries such as pandas, NumPy, Scikit-learn
Experience with Python GenAI frameworks (e.g., LangChain, LangGraph) is a plus
Familiarity with CI/CD workflows in GitLab is a plus
Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana) is a plus
Familiarity with gRPC for high-performance service communication is a plus
Familiarity with Model Context Protocol (MCP) is a plus
Familiarity with AI observability and tracing tools (e.g., Langfuse) is a plus
Originally posted on Himalayas
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