AI and Agent Engineer - Senior Associate

Weaver

Bengaluru

On-site

INR 1,200,000 - 1,800,000

Full time

2 days ago
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Job summary

Weaver seeks an AI and Agent Engineer - Senior Associate to build production-ready AI-enabled applications across the Microsoft stack. You will design, implement, and monitor AI agents, integrate with Graph, SharePoint, Teams, and Dataverse, and establish robust evaluation and governance for prompts, tools, and behavior.

The role emphasizes engineering production systems, optmizing performance, and responsible AI controls in enterprise environments, with a focus on integration, testing, and

Qualifications

  • 5+ years of software, integration, automation, or data application development.
  • Proven production experience with generative AI or conversational AI applications.
  • Experience building applications across Copilot Studio, Power Platform, and Azure.
  • Familiarity with orchestration frameworks such as Semantic Kernel.

Responsibilities

  • Develop, test, deploy, and monitor AI-enabled applications and agents across the Microsoft ecosystem.
  • Integrate AI solutions with Microsoft Graph, SharePoint, Teams, Dataverse, Power Platform, and enterprise systems.
  • Engineer behavior: prompts, grounding logic, response structures, escalation rules, and model routing.
  • Automate testing, evaluation, and incident regression for AI agents and workflows.
  • Instrument solutions for usage, latency, cost, and reliability; review telemetry and incidents.

Skills

REST APIs
OAuth
OpenAPI
CI/CD
Application Insights
Azure Monitor
Troubleshooting
Prompts & Instructions

Tools

Microsoft Graph
Dataverse
SharePoint
Teams
Azure
Power Platform
Semantic Kernel

Job description

AI and Agent Engineer - Senior Associate

The Senior AI and Agent Engineer will develop, integrate, test, deploy, and monitor AI-enabled applications and agents across the Microsoft ecosystem. The role is responsible for the intelligence, orchestration, actions, integrations, and behavioral quality of AI solutions.

This is an AI application engineering role, not a prompt-writing position. The successful candidate must be able to build production software, integrate enterprise systems, create evaluation frameworks, troubleshoot complex behavior, and operate deployed solutions.

Primary Responsibilities

AI and agent development

  • Build and configure Copilot Studio agents, topics, actions, triggers, workflows, and generative orchestration.
  • Implement retrieval-augmented generation, structured outputs, tool use, multistep orchestration, and human approval patterns.
  • Develop custom APIs, Azure Functions, connectors, and supporting application services.
  • Integrate AI solutions with Microsoft Graph, SharePoint, Teams, Dataverse, Power Platform, and approved enterprise systems.

Prompt, context, and behavior engineering

  • Develop system instructions, prompts, grounding logic, response structures, fallback behavior, and escalation rules.
  • Implement model selection and routing based on accuracy, risk, latency, and consumption requirements.
  • Design agent behavior that distinguishes between answering, recommending, requesting clarification, escalating, and taking action.
  • Maintain version control for prompts, instructions, tools, actions, and model configurations.

Testing and evaluation

  • Develop evaluation datasets with practice SMEs.
  • Automate tests for groundedness, relevance, completeness, citation quality, task completion, response consistency, and escalation behavior.
  • Perform adversarial testing involving prompt injection, data leakage, unsupported instructions, excessive agency, and unauthorized actions.
  • Build regression tests to detect changes caused by models, prompts, source content, integrations, or application releases.
  • Document known limitations and expected failure behavior.

Operations and improvement

  • Instrument solutions for usage, latency, failures, cost, task completion, user feedback, and model behavior.
  • Review production telemetry and interaction patterns.
  • Investigate incidents and implement corrective changes.
  • Optimize token consumption, retrieval performance, application latency, and integration reliability.
  • Develop reusable agent templates, integration components, evaluation harnesses, and error-handling patterns.

Required Technical Skills

  • REST APIs, JSON, OAuth, OpenAPI, webhooks, and event-driven integration.
  • Microsoft Graph, Dataverse, SharePoint, and Teams integration.
  • Retrieval-augmented generation, embeddings, vector search, semantic search, hybrid search, reranking, and structured generation.
  • Agent orchestration, state management, tool invocation, and human-in-the-loop controls.
  • Automated testing, Git, pull requests, CI/CD, and production troubleshooting.
  • Application Insights, Azure Monitor, logging, alerting, and performance diagnostics.
  • Understanding of prompt injection, data exfiltration, overreliance, hallucination, unsafe actions, and AI-specific failure modes.

Preferred Experience

  • 5 or more years of software, integration, automation, or data application development.
  • Demonstrated production experience with generative AI or conversational AI applications.
  • Experience building applications across Copilot Studio, Power Platform, and Azure.
  • Familiarity with Semantic Kernel or comparable orchestration frameworks.
  • Basic C# experience within the Microsoft ecosystem.
  • Experience in regulated, confidential, or professional-services environments.

Success Measures

  • Evaluation performance against approved acceptance thresholds.
  • Task-completion and appropriate-escalation rates.
  • Production defect and regression rates.
  • Retrieval and grounding quality.
  • Response latency and cost per transaction.
  • Integration reliability.
  • Reuse of standard components.
  • Completeness of technical documentation and automated testing.
  • Speed and effectiveness of incident remediation.

This role engineers the behavior of AI applications. Practice SMEs remain accountable for defining and validating authoritative professional content, business rules, acceptable conclusions, and circumstances requiring human review.

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