AI Application Engineer

Ramsporia Services; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Ramsporia Services in the United States is seeking a senior software engineer to design, develop, and deploy enterprise AI applications using Large Language Models. You will build intelligent assistants and automation for complex engineering workflows, and develop Retrieval-Augmented Generation solutions using internal data sources.

The role requires strong Python, REST API experience (FastAPI or similar), and familiarity with distributed systems, Git, CI/CD, Docker, Kubernetes, and cloud

Qualifications

• BS/BA in CS, IT, engineering or equivalent practical experience.
• 5+ years of software engineering experience.
• Strong Python proficiency and API development experience.
• Hands-on with REST APIs using FastAPI or similar.
• Knowledge of distributed systems, Git, CI/CD, and containerization.

Responsibilities

• Design, develop, and deploy enterprise AI applications using LLMs.
• Build intelligent AI assistants and automation for engineering workflows.
• Develop RAG solutions using enterprise knowledge sources.
• Design AI agents for multi-step workflows via APIs and tools.
• Integrate AI apps with enterprise platforms, cloud services, and REST APIs.
• Create secure, scalable, production AI solutions with governance standards.
• Evaluate AI quality with prompt engineering, retrieval optimization, and guardrails.
• Collaborate across cloud, platform engineering, and security teams to find new use cases.
• Stay current with emerging AI tech and advocate business-value solutions.

Skills

Python

5+ years experience

REST APIs

Git

CI/CD

Docker

Kubernetes

Distributed systems

Prompt engineering

AI fundamentals

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent practical experience

Tools

FastAPI

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Pinecone

Weaviate

Milvus

pgvector

Job description

Role & responsibilities

• Design, develop, and deploy enterprise AI applications using Large Language Models (LLMs).


• Build intelligent AI assistants and automation solutions for engineering and operational workflows.


• Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources and internal documentation.


• Design and implement AI agents capable of performing multi-step workflows using APIs and external tools.


• Integrate AI applications with enterprise platforms, cloud services, databases, and REST APIs.


• Develop secure, scalable, production-ready AI solutions following enterprise security and governance standards.


• Evaluate and improve AI application quality through prompt engineering, retrieval optimization, model evaluation, and guardrails.


• Collaborate with cross-functional teams to identify and implement new AI use cases across cloud engineering, platform engineering, and security.


• Stay current with emerging AI technologies and recommend innovative solutions that deliver business value.

Preferred candidate profile

• Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent practical experience.


• 5+ years of software engineering experience.


• Strong proficiency in Python.


• Experience building REST APIs using FastAPI or similar frameworks.


• Strong understanding of software design patterns and distributed systems.


• Experience with Git, automated testing, and CI/CD pipelines.


• Experience developing containerized applications using Docker.


• Familiarity with Kubernetes and cloud-native application development.

Generative AI (hands-on experience required)

• Large Language Models OpenAI, Azure OpenAI, Gemini, Claude, or similar.


• Prompt engineering.


• Retrieval-Augmented Generation (RAG).


• Embeddings and semantic search.


• Vector databases.


• AI agents / agentic AI.


• Function calling / tool calling.


• AI application evaluation and optimization.


• AI safety, guardrails, and hallucination reduction.

Cloud & Enterprise Technologies

• Experience with one or more public cloud platforms: Microsoft Azure, Google Cloud Platform (GCP), or Amazon Web Services (AWS).


• Working knowledge of Identity and Access Management (IAM), cloud security best practices, REST APIs, enterprise authentication and authorization, infrastructure automation, and cloud governance.

Preferred Qualifications

Experience with one or more of the following:

• Frameworks: LangChain, LangGraph, LlamaIndex, Semantic Kernel.


• Model Context Protocol (MCP).


• AI platforms: Azure AI Foundry, Google Vertex AI.


• Vector databases: Pinecone, Weaviate, Milvus, pgvector, or similar.


• Data stores: PostgreSQL, Redis.


• Infrastructure and orchestration: Terraform, GitHub Actions, Airflow.


• CSPM tools such as Wiz, Prisma Cloud, or Orca.


• Enterprise chat platform integrations such as Microsoft Teams Bot Framework or Slack apps.


• Regulated or healthcare environment experience, including HIPAA awareness.