A
Custom Software Engineer
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Custom Software Engineer
Accenture- Posted 5 hours ago
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Job Description
Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : AI Agents & Workflow Integration
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
We are seeking an AI Engineer to support the build, testing and deployment of the Digital Brain foundation and suite of AI agents transforming Product Design and requirements development across the SDLC.
Working alongside Senior AI Engineers, Product Owners and Architects, the role will be hands-on in developing knowledge integrations, agent capabilities and production-ready AI solutions across Product Design, Feature Generation, User Story Generation and Strategic Prioritisation.
Key Responsibilities
Build and enhance components of the Digital Brain, integrating product and engineering knowledge from sources such as Confluence, Jira, Git, Miro, Figma and release documentation.
Develop and maintain data pipelines, APIs and integrations supporting the knowledge and traceability layer.
Build and configure AI agents for Product Design, Feature Generation, User Story Generation and Strategic Prioritisation.
Develop RAG and knowledge-retrieval capabilities to provide agents with accurate enterprise context.
Implement prompts, tools, workflows and agent behaviours using established engineering patterns and frameworks.
Support development of end-to-end traceability across product designs, features, user stories, systems and production code.
Build and execute automated evaluations and tests covering accuracy, hallucination, completeness, consistency and traceability.
Investigate defects and improve agent performance based on testing and user feedback.
Integrate AI capabilities into existing Product and Engineering tools and workflows.
Participate in rapid prototyping and user testing, iterating solutions against live use cases.
Contribute reusable components, documentation, engineering standards and CI/CD pipelines.
Work closely with Senior Engineers, Product Owners, Architects and users while progressively taking ownership of individual components and agent capabilities.
Core Skills
Software engineering experience, ideally Python and/or TypeScript/Java
Understanding of LLMs, Generative AI and agentic AI concepts
Experience or exposure to Spec Driven Development (SDD)
Experience or exposure to RAG and knowledge retrieval
Familiarity with agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI or Semantic Kernel
Exposure to vector databases and/or knowledge graphs
API development and system integration
Prompt and context engineering
Automated testing and AI evaluation techniques
Git, DevOps and CI/CD practices
Experience or familiarity with tools such as Jira, Confluence and GitHub/GitLab
Understanding of the software development lifecycle and Agile product delivery
Strong problem-solving skills and willingness to learn emerging AI engineering technologies
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : AI Agents & Workflow Integration
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
We are seeking an AI Engineer to support the build, testing and deployment of the Digital Brain foundation and suite of AI agents transforming Product Design and requirements development across the SDLC.
Working alongside Senior AI Engineers, Product Owners and Architects, the role will be hands-on in developing knowledge integrations, agent capabilities and production-ready AI solutions across Product Design, Feature Generation, User Story Generation and Strategic Prioritisation.
Key Responsibilities
Build and enhance components of the Digital Brain, integrating product and engineering knowledge from sources such as Confluence, Jira, Git, Miro, Figma and release documentation.
Develop and maintain data pipelines, APIs and integrations supporting the knowledge and traceability layer.
Build and configure AI agents for Product Design, Feature Generation, User Story Generation and Strategic Prioritisation.
Develop RAG and knowledge-retrieval capabilities to provide agents with accurate enterprise context.
Implement prompts, tools, workflows and agent behaviours using established engineering patterns and frameworks.
Support development of end-to-end traceability across product designs, features, user stories, systems and production code.
Build and execute automated evaluations and tests covering accuracy, hallucination, completeness, consistency and traceability.
Investigate defects and improve agent performance based on testing and user feedback.
Integrate AI capabilities into existing Product and Engineering tools and workflows.
Participate in rapid prototyping and user testing, iterating solutions against live use cases.
Contribute reusable components, documentation, engineering standards and CI/CD pipelines.
Work closely with Senior Engineers, Product Owners, Architects and users while progressively taking ownership of individual components and agent capabilities.
Core Skills
Software engineering experience, ideally Python and/or TypeScript/Java
Understanding of LLMs, Generative AI and agentic AI concepts
Experience or exposure to Spec Driven Development (SDD)
Experience or exposure to RAG and knowledge retrieval
Familiarity with agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI or Semantic Kernel
Exposure to vector databases and/or knowledge graphs
API development and system integration
Prompt and context engineering
Automated testing and AI evaluation techniques
Git, DevOps and CI/CD practices
Experience or familiarity with tools such as Jira, Confluence and GitHub/GitLab
Understanding of the software development lifecycle and Agile product delivery
Strong problem-solving skills and willingness to learn emerging AI engineering technologies
More Info
Key Skills
AI Agents
agentic AI concepts
knowledge graphs
vector databases
LangGraph
Workflow Integration
LangChain
CrewAI
Generative AI
LLMs
Spec Driven Development (SDD)
context engineering
Semantic Kernel
AutoGen
knowledge retrieval
RAG
AI evaluation techniques
CI CD practices
Agile product delivery
About Company
