LogicApps – Agentic AI Engineer

Job Description

LogicApps is looking for a highly skilled and forward-thinking Agentic AI Engineer who can lead the next generation of AI-assisted software development workflows. This role is ideal for professionals who understand how to combine engineering expertise with modern AI coding ecosystems to deliver scalable, production-ready applications. Unlike traditional software engineering positions, this opportunity focuses heavily on orchestrating AI coding agents, reviewing AI-generated output, debugging multi-system production issues, and ensuring that every layer of the technology stack functions efficiently. Candidates applying for this role should possess hands-on experience with AI-driven engineering workflows and should be comfortable working across frontend, backend, APIs, databases, automation pipelines, and observability systems.

As an Agentic AI Engineer, you will act as the technical backbone of a delivery pod where AI coding tools are deeply integrated into the software development lifecycle. The organization expects engineers to guide AI agents strategically rather than manually writing every line of code. This role requires strong decision-making abilities, architectural thinking, and the capability to identify issues that AI tools may overlook, including security vulnerabilities, scalability bottlenecks, inefficient database operations, and cross-platform integration challenges. Professionals in this position will also be responsible for defining specifications, validating AI-generated code quality, tuning AI-assisted review systems, and ensuring compliance with modern engineering standards such as CI/CD, automated testing, and observability.

The ideal candidate for this AI engineering role should already be actively using modern AI coding assistants and autonomous coding agents in real-world production environments. LogicApps values engineers who understand when to rely on AI-generated automation and when human oversight becomes critical. The company is specifically seeking individuals who can create structured specifications, define measurable acceptance criteria, implement evaluation-driven development practices, and improve software reliability through intelligent AI orchestration. This role offers excellent exposure to emerging technologies such as Model Context Protocol (MCP), AI evaluation frameworks, prompt engineering, AI-assisted code reviews, and autonomous development systems, making it an outstanding career opportunity for professionals looking to build expertise in advanced AI-native software engineering.

Roles & Responsibilities

• Direct AI coding agents and development assistants to generate scalable, production-grade software across frontend, backend, and database systems while maintaining engineering quality standards.
• Review and validate AI-generated code thoroughly before deployment to identify logical flaws, security gaps, architectural inconsistencies, and performance bottlenecks that automated systems may miss.
• Design and maintain technical specifications that clearly define project goals, non-goals, acceptance criteria, and expected system behavior for AI-assisted implementation workflows.
• Collaborate with cross-functional engineering teams to debug complex production issues involving APIs, databases, microservices, integrations, and cloud infrastructure environments.
• Configure and optimize AI-powered code review tools to ensure meaningful issue detection and reduce false-positive reporting during development cycles.
• Build and improve evaluation frameworks for AI-generated outputs by integrating automated testing, observability tools, and quality assurance pipelines into delivery workflows.
• Participate in architecture planning discussions and ensure all technical decisions align with scalability, maintainability, security, and compliance requirements.
• Mentor junior engineers and help them improve their AI tool fluency, prompt engineering practices, debugging skills, and AI-assisted software development methodologies.
• Work closely with DevOps and platform engineering teams to maintain CI/CD pipelines, automated deployments, infrastructure monitoring, and production reliability standards.
• Identify AI-generated security vulnerabilities such as SQL injection risks, prompt injection attacks, insecure authentication flows, and exposed secrets before release.
• Improve development efficiency by implementing AI-driven engineering workflows, reusable prompts, agent harness configurations, and autonomous coding best practices.
• Stay updated with the latest advancements in AI-assisted development tools, autonomous agents, software architecture patterns, and modern engineering practices.

Requirements & Eligibility

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or equivalent practical industry experience with strong technical problem-solving skills.
• Minimum 1–3 years of hands-on software engineering experience with practical exposure to AI-native development workflows and production-level application development.
• Daily working experience with at least two AI coding tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, Aider, Tabnine, Continue.dev, or JetBrains AI Assistant.
• Strong understanding of frontend technologies, backend frameworks, APIs, databases, cloud systems, and distributed architecture required for full-stack debugging and AI orchestration.
• Practical experience using AI-driven code review platforms including GitHub Copilot Code Review, CodeRabbit, Qodo, Greptile, or similar intelligent review systems.
• Ability to write highly effective prompts for AI coding tools by defining project context, architectural constraints, formatting expectations, and output validation rules.
• Familiarity with autonomous AI agents capable of executing multi-step engineering tasks such as code generation, testing, debugging, and pull request creation.
• Strong understanding of software security concepts including prompt injection prevention, SQL injection risks, secure coding practices, access control, and data protection strategies.
• Experience working with CI/CD pipelines, Git workflows, automated testing frameworks, observability platforms, and modern software engineering best practices.
• Knowledge of Model Context Protocol (MCP), AI evaluation frameworks, audit logging, monitoring systems, and AI governance practices will be considered an added advantage.

Expected Salary

The expected salary for the Agentic AI Engineer role at LogicApps typically ranges between ₹8 LPA to ₹18 LPA for candidates with 1–3 years of experience, depending on technical expertise, AI tooling exposure, and full-stack engineering capabilities. Professionals with strong experience in AI-assisted software development, prompt engineering, autonomous coding agents, and production debugging may receive higher compensation packages. Additional performance bonuses, learning opportunities, and exposure to advanced AI technologies can further enhance the overall career value of this position.

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