A
Custom Software Engineer
A
Custom Software Engineer
Accenture7-9 Years
- Posted 6 hours ago
- Be among the first 10 applicants
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 : Generative AI
Good to have skills : AI Agents & Workflow Integration
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Core Engineering & Day to Day Practice
Strong Python fundamentals
Hands-on experience using Claude Code for day-to-day development and coding workflows
Agentic Systems & Architecture
Proficiency with agentic frameworks (e.g., LangGraph, custom orchestration patterns) — not just chatbot/RAG experience
Experience selecting, integrating, and evaluating LLM APIs (e.g., Anthropic, OpenAI, others), including assessing tradeoffs across models and providers
Proficiency with agentic planning and tool-use patterns (ReAct, Chain-of-Thought + action) experience building and shipping multi-agent pipelines in production, including handling failure modes, loops, and hallucinations
Ability to design prompts systematically as part of end-to-end agent behavior
Comfort with async, event-driven architectures
Memory & Retrieval Architecture
Experience designing agent memory architectures, including short- and long-term memory, embeddings, vector databases, and context window/token management
Experience building and operating production RAG systems, including horizontally scalable vector databases, with attention to latency, reliability, and throughput tradeoffs
Evaluation & Human in the Loop
Ability to define task-specific evals and regression tests to catch prompt drift, retrieval failures, and behavioral regressions
Understanding of online vs. offline evaluation tradeoffs and using results to drive iterative improvements
Experience with human-in-the-loop (HITL) design and evaluation, including approval gating, routing ambiguous outputs to humans, and closing the feedback loop (e.g., Langfuse human annotation evals)
Integration, Governance & Security
Experience with MCP server integration
Experience integrating agents with enterprise systems (internal APIs, identity/auth layers)
Understanding of AI governance: audit trails, explainability, access controls, and data residency constraints
Security-conscious agent design: scoped permissions and prompt injection mitigation
Bonus: Experience operating within IT governance or change management processes
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 : Generative AI
Good to have skills : AI Agents & Workflow Integration
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Core Engineering & Day to Day Practice
Strong Python fundamentals
Hands-on experience using Claude Code for day-to-day development and coding workflows
Agentic Systems & Architecture
Proficiency with agentic frameworks (e.g., LangGraph, custom orchestration patterns) — not just chatbot/RAG experience
Experience selecting, integrating, and evaluating LLM APIs (e.g., Anthropic, OpenAI, others), including assessing tradeoffs across models and providers
Proficiency with agentic planning and tool-use patterns (ReAct, Chain-of-Thought + action) experience building and shipping multi-agent pipelines in production, including handling failure modes, loops, and hallucinations
Ability to design prompts systematically as part of end-to-end agent behavior
Comfort with async, event-driven architectures
Memory & Retrieval Architecture
Experience designing agent memory architectures, including short- and long-term memory, embeddings, vector databases, and context window/token management
Experience building and operating production RAG systems, including horizontally scalable vector databases, with attention to latency, reliability, and throughput tradeoffs
Evaluation & Human in the Loop
Ability to define task-specific evals and regression tests to catch prompt drift, retrieval failures, and behavioral regressions
Understanding of online vs. offline evaluation tradeoffs and using results to drive iterative improvements
Experience with human-in-the-loop (HITL) design and evaluation, including approval gating, routing ambiguous outputs to humans, and closing the feedback loop (e.g., Langfuse human annotation evals)
Integration, Governance & Security
Experience with MCP server integration
Experience integrating agents with enterprise systems (internal APIs, identity/auth layers)
Understanding of AI governance: audit trails, explainability, access controls, and data residency constraints
Security-conscious agent design: scoped permissions and prompt injection mitigation
Bonus: Experience operating within IT governance or change management processes
More Info
Key Skills
Generative AI
production RAG systems
Memory Retrieval Architecture
Claude Code
async event-driven architectures
security-conscious agent design
LLM APIs
Agentic Systems Architecture
agentic planning
AI governance
tool-use patterns
agentic frameworks
Human in the Loop
MCP server integration
Python fundamentals
About Company
