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successfactors

Subcontractor

Birlasoft
Bengaluru, IND
Mid
Onsite
Discovered 1 weeks ago
awsazuregcplangchainpython

Full Job Posting

Key Responsibilities

  • Skills Required –
  • Design, develop, and implement Generative AI solutions to address business and technical challenges.
  • Build and integrate AI agents, workflows, and orchestration frameworks for enterprise use cases.
  • Develop proof-of-concepts (POCs) and prototypes to validate GenAI capabilities and business value.
  • Collaborate with cross-functional teams to gather requirements and translate them into scalable AI solutions.
  • Implement, test, and optimize LLM-based applications, including prompt engineering, RAG, and agent-based systems.
  • Identify potential risks, edge cases, and performance considerations during solution design and implementation.
  • Support deployment, monitoring, and continuous improvement of AI applications in production environments.
  • Troubleshoot technical issues, take ownership of problem resolution, and drive solutions to completion.
  • Stay current with emerging trends, tools, and best practices in Generative AI and agentic AI systems.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Strong programming skills, preferably in Python, with the ability to design and implement efficient solutions.
  • Hands-on experience building Generative AI applications and agent-based systems.
  • Good understanding of LLMs, prompt engineering, RAG architectures, and AI orchestration frameworks.
  • Experience developing and delivering POCs and technical prototypes.
  • Familiarity with cloud platforms such as Azure, AWS, or GCP.
  • Strong analytical and problem-solving skills.
  • Ability to work independently and take ownership of technical challenges.
  • Good communication and collaboration skills.
  • Demonstrated eagerness to learn new technologies and adapt to evolving AI ecosystems.

Preferred Skills

  • Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar agent frameworks.
  • Knowledge of vector databases, embeddings, and retrieval systems.
  • Understanding of application scalability, monitoring, and production deployment considerations.
  • Experience in evaluating AI solutions for reliability, performance, and business impact.
  • Exposure to handling edge cases, failure scenarios, and responsible AI practices.

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