Senior
We are seeking a highly skilled Agentic AI Developer with 5+ years of experience in deign, develop, and deploy intelligent AI solutions that drive business transformation and innovation. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), AI agent frameworks, and modern software engineering practices. This role requires hands-on experience in building scalable, secure, and production-ready AI systems aligned with enterprise objectives.
Design, develop, and implement AI agents for enterprise business use cases.
Build intelligent workflows leveraging LLMs, tools, APIs, memory management, and human-in-the-loop approval mechanisms.
Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories and structured/unstructured data sources.
Integrate AI solutions with enterprise applications, databases, APIs, and knowledge management systems.
Create and maintain reusable prompts, tools, templates, and workflow components.
Evaluate AI solutions for accuracy, reliability, safety, latency, scalability, and cost efficiency.
Apply machine learning techniques and statistical methods where appropriate.
Deploy, monitor, troubleshoot, and continuously optimize AI applications in production environments.
Ensure compliance with security, privacy, governance, and Responsible AI standards.
Collaborate closely with architects, developers, product owners, and business stakeholders to deliver innovative AI solutions.
Contribute to AI solution architecture, technical design, and best practice frameworks.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.
5+ years of experience in software development, AI solution design, or enterprise application development.
Strong programming expertise in Python.
Hands-on experience with Generative AI, Large Language Models (LLMs), and AI application development.
Experience designing and building AI Agents, autonomous workflows, and multi-agent systems.
Strong understanding of Retrieval-Augmented Generation (RAG) architectures.
Experience with embeddings, vector databases, semantic search, and knowledge retrieval systems.
Solid understanding of machine learning concepts, model evaluation, and statistical techniques.
Experience working with REST APIs, databases, Git, testing frameworks, and CI/CD pipelines.
Knowledge of cloud platforms such as Azure, AWS, or Google Cloud Platform.
Experience with Docker, containerization, and enterprise integrations.
Strong analytical, problem-solving, and troubleshooting skills.
Excellent verbal and written communication skills.
Experience with AI orchestration frameworks such as:
Experience with workflow orchestration platforms such as Temporal.
Knowledge of Model Context Protocol (MCP).
Experience with AI observability, evaluation frameworks, guardrails, and responsible AI implementation.
Familiarity with prompt engineering, agent memory management, and tool-calling architectures.
Experience integrating AI solutions with enterprise platforms such as:
Knowledge of MLOps and AI deployment best practices.
Experience working in telecom, manufacturing, automotive, or large-scale enterprise environments.
Microsoft Azure AI certifications or equivalent AI certifications.
Experience with Fine-Tuning, Prompt Optimization, and AI Governance frameworks.
Exposure to Knowledge Graphs and Graph-based RAG architectures.
Experience with multi-modal AI applications involving text, image, and document intelligence.
Contribution to open-source AI projects or communities.
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We are seeking a highly skilled Agentic AI Developer with 5+ years of experience to design, develop, and deploy intelligent AI solutions that drive business transformation and innovation. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), AI agent frameworks, and modern software engineering practices. This role requires hands-on experience in building scalable, secure, and production-ready AI systems aligned with enterprise objectives.
Design, develop, and implement AI agents for enterprise business use cases
Build intelligent workflows leveraging LLMs, tools, APIs, memory management, and human-in-the-loop approval mechanisms
Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories and structured/unstructured data sources
Integrate AI solutions with enterprise applications, databases, APIs, and knowledge management systems
Create and maintain reusable prompts, tools, templates, and workflow components
Evaluate AI solutions for accuracy, reliability, safety, latency, scalability, and cost efficiency
Apply machine learning techniques and statistical methods where appropriate
Deploy, monitor, troubleshoot, and continuously optimize AI applications in production environments
Ensure compliance with security, privacy, governance, and Responsible AI standards
Collaborate closely with architects, developers, product owners, and business stakeholders to deliver innovative AI solutions
Contribute to AI solution architecture, technical design, and best practice frameworks
We are seeking a highly skilled Agentic AI Developer with 5+ years of experience in designing, developing, and deploying intelligent AI solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), AI agent frameworks, and modern software engineering practices, with hands-on experience in building scalable, secure, and production-ready AI systems.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field
5+ years of experience in software development, AI solution design, or enterprise application development
Strong programming expertise in Python
Hands-on experience with Generative AI
Hands-on experience with Large Language Models (LLMs)
Hands-on experience with AI application development
Experience designing and building AI Agents
Experience designing and building autonomous workflows
Experience designing and building multi-agent systems
Strong understanding of Retrieval-Augmented Generation (RAG) architectures
Experience with embeddings
Experience with vector databases
Experience with semantic search
Experience with knowledge retrieval systems
Solid understanding of machine learning concepts
Solid understanding of model evaluation
Solid understanding of statistical techniques
Experience working with REST APIs
Experience working with databases
Experience working with Git
Experience working with testing frameworks
Experience working with CI/CD pipelines
Knowledge of cloud platforms such as Azure, AWS, or Google Cloud Platform
Experience with Docker
Experience with containerization
Experience with enterprise integrations
Strong analytical skills
Strong problem-solving skills
Strong troubleshooting skills
Excellent verbal communication skills
Excellent written communication skills
Experience with AI orchestration frameworks such as LangGraph
Experience with AI orchestration frameworks such as LangChain
Experience with AI orchestration frameworks such as Semantic Kernel
Experience with AI orchestration frameworks such as AutoGen
Experience with AI orchestration frameworks such as CrewAI
Experience with workflow orchestration platforms such as Temporal
Knowledge of Model Context Protocol (MCP)
Experience with AI observability
Experience with evaluation frameworks
Experience with guardrails
Experience with responsible AI implementation
Familiarity with prompt engineering
Familiarity with agent memory management
Familiarity with tool-calling architectures
Experience integrating AI solutions with SharePoint
Experience integrating AI solutions with Jira
Experience integrating AI solutions with ServiceNow
Experience integrating AI solutions with Microsoft Teams
Experience integrating AI solutions with SAP
Knowledge of MLOps
Knowledge of AI deployment best practices
Experience working in telecom environments
Experience working in manufacturing environments
Experience working in automotive environments
Experience working in large-scale enterprise environments
Microsoft Azure AI certifications or equivalent AI certifications
Experience with Fine-Tuning
Experience with Prompt Optimization
Experience with AI Governance frameworks
Exposure to Knowledge Graphs
Exposure to Graph-based RAG architectures
Experience with multi-modal AI applications involving text, image, and document intelligence
Contribution to open-source AI projects or communities
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