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Agentic AI developer

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Onsite

Agentic AI developer

Thoughtscrest Software

Agentic AI developer

Skills

Google Cloud PlatformDockerPythonData ScienceMicroservicesMachine LearningAIAWSKubernetesNo-code AutomationsGDPRAzure

6 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

14 October 2026

What they need


Job Title: Agentic AI Developer / Senior Agentic AI Developer
Location: Bangalore
Work Mode: Work From Office (WFO)
Company: Thoughtscrest Software Solutions Pvt. Ltd.
Experience: 510 Years
Employment Type: Full-Time
Industry: Information Technology, AI/ML, Fintech

Interview Mode: Inperson Interview

About the Company

Thoughtscrest Software is a technology solutions company specializing in banking, fintech, and enterprise software. We are expanding our AI capabilities to build intelligent, autonomous, and scalable Agentic AI solutions that transform business operations, automate complex workflows, and enable intelligent decision-making.

Role Overview

We are looking for an experienced Agentic AI Developer with 5–10 years of overall software development experience, including a minimum of 2 years of hands-on experience in Agentic AI development.

The ideal candidate must have proven experience designing, developing, deploying, and maintaining Agentic AI solutions in production environments.

This role requires strong technical expertise in LLMs, AI agent frameworks, tool orchestration, API integrations, and enterprise-grade AI application development.

We are specifically looking for candidates who have moved beyond experimentation and POCs and have successfully delivered AI solutions used in real-world business environments.

Key Responsibilities:

1. Agentic AI Development

  • Design, develop, and deploy production-grade Agentic AI solutions using LLMs and modern agent orchestration frameworks.
  • Build autonomous AI agents capable of reasoning, planning, decision-making, and executing complex business workflows.
  • Develop single-agent and multi-agent architectures for enterprise applications.
  • Implement agent memory, context management, tool calling, and workflow orchestration.

2. Production Deployment & Scalability

  • Take Agentic AI solutions from concept and development through production deployment.
  • Build reliable, scalable, and maintainable AI applications that support real-world business operations.
  • Implement monitoring, logging, error handling, retries, and fallback mechanisms.
  • Optimize LLM performance, latency, token consumption, and operational costs.
  • Troubleshoot and resolve issues in production AI systems.

3. Integration & Enterprise Applications

  • Integrate AI agents with enterprise applications, REST APIs, databases, and external services.
  • Develop AI-powered automation solutions that interact with business systems.
  • Implement Retrieval-Augmented Generation (RAG), vector databases, and knowledge retrieval mechanisms where required.
  • Ensure appropriate security, access controls, and data protection mechanisms.

4. Collaboration & Solution Delivery

  • Work closely with business analysts, product managers, and engineering teams to translate business requirements into AI-driven solutions.
  • Evaluate AI frameworks, models, and architectures to identify suitable approaches.
  • Contribute to architectural decisions, technical design, and engineering best practices.
  • Mentor junior developers and contribute to building the organization's Agentic AI capabilities.

Required Skills & Qualifications:

Mandatory Requirements

Experience

  • 5–10 years of overall software development experience.
  • Minimum 2 years of hands-on experience developing Agentic AI applications.
  • Mandatory experience building and deploying at least one Agentic AI solution into a live production environment.
  • Experience supporting, monitoring, optimizing, and maintaining AI solutions after production deployment.
  • Strong hands-on software engineering and problem-solving capabilities.

Technical Skills

  • Strong proficiency in Python and backend application development.

  • Hands-on experience with LLMs and APIs such as OpenAI, Anthropic Claude, or other enterprise LLM platforms.

  • Practical experience with at least one Agentic AI framework such as:

  • LangGraph / LangChain

  • CrewAI

  • AutoGen

  • LlamaIndex

  • Other equivalent agent orchestration frameworks

  • Strong understanding of Agentic AI concepts, including:

  • Agent planning and reasoning

  • Tool calling and function execution

  • Multi-agent orchestration

  • Memory and context management

  • Workflow automation

  • Human-in-the-loop mechanisms

  • Experience integrating AI agents with REST APIs, databases, and enterprise applications.

  • Understanding of RAG architectures, embeddings, and vector databases.

  • Experience with Git, CI/CD pipelines, and software deployment practices.

  • Ability to design scalable, reliable, and secure AI applications.

Production Engineering Experience

Candidates must demonstrate practical experience with:

  • Deploying LLM-based or Agentic AI applications into production.
  • Handling production challenges such as reliability, latency, scalability, and error recovery.
  • Implementing observability, monitoring, logging, and troubleshooting mechanisms.
  • Managing LLM limitations, hallucinations, and response quality.
  • Evaluating and improving agent performance in real-world environments.

Candidates with experience limited to prototypes, hackathons, or proof-of-concept implementations without production deployments will not be considered.

Good to Have

  • Experience developing AI solutions for banking, financial services, or fintech.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with Docker, Kubernetes, and microservices architectures.
  • Experience building enterprise AI solutions involving complex workflows and business process automation.
  • Exposure to LLM evaluation frameworks, prompt optimization, and AI guardrails.
  • Experience with MCP (Model Context Protocol) and emerging agent interoperability standards.
  • Experience leading technical teams or mentoring developers.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.

What We Offer

  • Opportunity to work on cutting-edge Agentic AI solutions for banking and enterprise customers.
  • Hands-on involvement in building and deploying real-world AI products.
  • Exposure to modern LLM technologies, AI frameworks, and enterprise integrations.
  • Competitive compensation with performance-based incentives.
  • Opportunities for technical leadership and career growth.
  • Collaborative work environment focused on innovation and continuous learning.
  • Upskilling opportunities through internal training and learning support.

Important Selection Criteria

Candidates will be evaluated primarily on:

  1. Overall Experience: 5–10 years in software engineering.
  2. Agentic AI Experience: Minimum 2 years of hands-on Agentic AI development.
  3. Production Experience: Must have deployed at least one Agentic AI application into production.
  4. Technical Expertise: Strong Python development, agent frameworks, LLM integration, and orchestration skills.
  5. Solution Ownership: Ability to independently design, develop, deploy, troubleshoot, and maintain enterprise-grade Agentic AI solutions.

Note: Candidates must be prepared to explain the architecture, technologies, deployment approach, production challenges, and their individual contributions to Agentic AI solutions they have delivered.

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