N #1935
Applications open
Full-Time Job
Jr. Agentic AI Engineer
Proclink
About the role
Job Description : We are looking for passionate and experienced Agentic AI Engineers across Junior, Senior, and Lead levels to design, develop, and deploy next-generation AI agents using GitHub Copilot Agent SDK , Microsoft Agent Framework , and Python . The ideal candidate should have strong expertise in building autonomous and multi-agent systems, integrating LLMs, implementing Agentic AI workflows, and delivering enterprise-grade AI solutions. The role involves architecting intelligent agents, enabling agent-to-agent collaboration, integrating enterprise tools and data sources, implementing RAG solutions, and deploying scalable AI applications in cloud environments. Responsibilities Design, develop, and deploy AI agents using GitHub Copilot Agent SDK and Microsoft Agent Framework. Build autonomous, multi-agent, and workflow-driven AI solutions for enterprise use cases. Develop agent orchestration, tool-calling, function-calling, and human-in-the-loop workflows. Implement memory management, context handling, and agent communication patterns. Design and develop scalable backend services using Python and FastAPI. Build Retrieval-Augmented Generation (RAG) solutions using vector databases and semantic search techniques. Integrate AI agents with enterprise applications, APIs, databases, and external tools. Develop and optimize prompt engineering strategies for improved agent performance. Design, implement, and maintain CI/CD pipelines for AI agent deployments. Monitor, evaluate, and continuously improve agent performance, accuracy, and operational efficiency. Collaborate with cross-functional teams including Product, QA, Engineering, and DevOps teams. Contribute to architecture design, technical documentation, and best practices for Agentic AI development. Responsibilities Design,develop, and deploy AI agents using GitHub Copilot Agent SDK and Microsoft Agent Framework. Build autonomous, multi-agent, and workflow-driven AI solutions for enterprise use cases. Develop agent orchestration, tool-calling, function-calling, and human-in-the-loop workflows. Implement memory management, context handling, and agent communication patterns. Design and develop scalable backend services using Python and FastAPI. Build Retrieval-Augmented Generation (RAG) solutions using vector databases and semantic search techniques. Integrate AI agents with enterprise applications, APIs, databases, and external tools. Develop and optimize prompt engineering strategies for improved agent performance. Design, implement, and maintain CI/CD pipelines for AI agent deployments. Monitor,evaluate, and continuously improve agent performance, accuracy, and operational efficiency. Collaborate with cross-functional teams including Product, QA, Engineering, and DevOps teams. Contribute to architecture design, technical documentation, and best practices for Agentic AI development. Skills and Qualifications 2.5+ years of experience in software engineering and AI solution development. Strong hands-on experience in Python programming and software design principles. Experience developing AI agents using GitHub Copilot Agent SDK and/or Microsoft Agent Framework. Strong understanding of Agentic AI concepts, including autonomous agents, orchestration, memory, planning, and reasoning. Experience with Large Language Models (LLMs), prompt engineering, and AI application development. Hands-on experience building REST APIs using FastAPI or similar frameworks. Experience implementing Retrieval-Augmented Generation (RAG) solutions. Strong problem-solving, analytical, and debugging skills. Experience with version control systems such as Git and GitHub. Excellent communication, collaboration, and stakeholder management skills. Preferred Qualifications Experience with Microsoft AI Foundry, Prompt Flow, and AI model deployment. Knowledge of Azure OpenAI, Azure AI Services, and Azure cloud-native solutions. Experience with Vector Databases such as Azure AI Search, Understanding of Model Context Protocol (MCP) and tool integration frameworks. Hands-on experience with Docker, Kubernetes, and containerized deployments. Experience implementing enterprise-grade security, governance, and compliance controls for AI applications. Knowledge of DevOps practices, GitHub Actions, and CI/CD automation. Experience leading AI projects and mentoring engineering teams (Senior/Lead positions). Bachelors or masters degree in computer science, Artificial Intelligence, Data Science, or a related field. Nice to Have Hands-on experience with Microsoft AI Foundry Agent Services. Experience building multi-agent ecosystems and autonomous workflow platforms. Exposure to GitHub Copilot Extensions and enterprise AI integrations. Knowledge of modern AI evaluation, observability, and monitoring frameworks. Junior Agentic AI Engineer Strong Python fundamentals. Basic experience with LLMs and AI agent development. API integration and workflow automation experience. Ability to develop and support enterprise AI agents under guidance.
Eligibility & process
Who can apply
Experience: 3-5 Yrs. Open to matching qualifications.
Skills & stack
Selection process
- Online Assessment / Technical Interview Rounds / HR Review
Prep kit
20 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for Proclink and tech roles.
Technical Placement Cheat Sheets & Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
APTITUDE & LOGIC
Aptitude Practice Questions & Online Mock Tests
Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.
COMPANY GUIDE
Proclink Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Proclink and off-campus tech roles.
MOCK TESTS & PAPERS
Comprehensive Interview Prep Resources & Syllabus
Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (API, Artificial Intelligence, SQL, Python, Machine, Machine learning, SDK, Github) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Proclink Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Proclink as a Jr. Agentic AI Engineer?
Highlight Proclink's market reputation, recent tech innovations, and how your skills in API directly solve their team's objectives.
Highlight Proclink's market reputation, recent tech innovations, and how your skills in API directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.