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JOB-AI-ENGINEER Data, AI & Analytics Engineering

AI Engineer

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The Opportunity

AI Engineer (overall, 6-10 years with at least 2 years of AI Dev experience)

Design, develop and deploy enterprise-grade AI solutions, including AI Agents, RAG-based applications, Intelligent Automation workflows and LLM-powered platforms. The candidate will work closely with Architects, Product Owners, Data Engineers, and Business Stakeholders to build scalable, secure, and production-ready AI systems that integrate with enterprise applications and data platforms. This role requires both strong software engineering capabilities and practical expertise in Generative AI technologies.

AI Agent Development

· Design and implement autonomous and semi-autonomous AI Agents

· Implement tool calling and function calling capabilities

· Create prompt templates and prompt optimization strategies

· Define agent workflows and state management

· Optimize retrieval accuracy and response quality

· Implement knowledge grounding mechanisms

· Integrate AI solutions with enterprise systems through APIs

· Consume and expose REST APIs

· Work with structured and unstructured data sources

· Build data pipelines for AI applications

· Deploy AI solutions in cloud environments

· Implement CI/CD pipelines for AI applications

Programming Languages

· Python (Mandatory)

· JavaScript / TypeScript

AI Frameworks - Experience with one or more:

  • LangChain
  • LangGraph

Backend Development

  • REST APIs
  • GraphQL
  • FastAPI

Cloud Platforms - Experience with AWS

  • Lambda
  • S3
  • ECS/EKS

What you'll do

  • Design and develop AI Agents, RAG applications, and intelligent automation solutions.
  • Build and optimize agent workflows, prompt strategies, and knowledge retrieval mechanisms.
  • Develop backend services and APIs using Python, FastAPI, REST APIs, and GraphQL.
  • Integrate AI solutions with enterprise applications, data platforms, and external systems.
  • Build and deploy cloud-native AI applications on AWS (Lambda, S3, ECS/EKS).
  • Implement CI/CD pipelines and follow software engineering best practices for scalable deployments.

What you'll bring

  • 6-10 years of software engineering experience, including at least 2 years of hands-on AI/Generative AI development experience.
  • Strong programming expertise in Python (mandatory) and working knowledge of JavaScript/TypeScript.
  • Experience building AI Agents, RAG-based solutions, LLM-powered applications, and other Generative AI solutions.
  • Hands-on experience with LangChain, LangGraph, or similar AI orchestration frameworks.
  • Strong understanding of RAG architectures, vector databases, embeddings, prompt engineering, and knowledge grounding techniques.
  • Experience developing and integrating REST APIs, GraphQL services, and FastAPI-based applications.
  • Cloud deployment experience on AWS, including Lambda, S3, ECS, and EKS.
  • Familiarity with enterprise integrations, API development, data pipelines, and working with structured and unstructured data sources.
  • Knowledge of CI/CD pipelines, containerization, and cloud-native architectures.
  • Ability to collaborate effectively with architects, data engineers, product owners, and business stakeholders.
  • Strong analytical, problem-solving, and communication skills with a focus on delivering scalable, secure, and production-ready AI solutions.

AI Fluency Expected

At Myridius, we expect AI fluency across all roles. This means the ability to effectively and responsibly use AI-enabled tools to improve productivity, quality, analysis, decision-making, documentation, testing, delivery, and problem-solving within one's function. All candidates should be comfortable working with AI as a day-to-day enabler while applying sound judgment, critical thinking, and accountability for outcomes.

Good to Have

  • Experience with Vector Databases such as Pinecone, Weaviate, Chroma, or FAISS.
  • Exposure to MLOps/LLMOps practices, including model monitoring, evaluation, and AI observability.
  • Experience with Docker, Kubernetes, and containerized AI application deployments.
  • Familiarity with Azure OpenAI, Amazon Bedrock, OpenAI APIs, or similar enterprise AI platforms.
  • Experience building multi-agent systems, intelligent automation workflows, and agent orchestration frameworks.
  • Working knowledge of machine learning concepts, embeddings, fine-tuning, and model evaluation techniques.
  • Experience with streaming data pipelines, event-driven architectures, and distributed systems.
  • Understanding of security, governance, responsible AI, and enterprise compliance requirements.
  • Exposure to DevOps best practices, Infrastructure as Code (Terraform/CloudFormation), and automated deployment pipelines.
  • Certification in AWS, Generative AI, or cloud-native technologies is a plus.

Ready to make an impact?

Submit your application today and join the Myridius team.

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