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Posted: 10/9/2026Python
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing agentic AI workflows, deploying large language models, and optimizing scalable APIs. Proven ability to lead technical teams and collaborate across business domains while ensuring the reliability and security of AI systems.
Highest-signal resume keywords
Agentic AI Workflow DesignLarge Language Model IntegrationPython ProgrammingDeep Learning FrameworksData Engineering Practices
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Lead the design and implementation of agentic AI workflows using LangGraph, AutoGen, LangChain, or similar frameworks
- Architect and optimize scalable REST/WebSocket APIs for production deployment
- Develop, fine-tune, and integrate large language models into enterprise applications
- Deploy and maintain at least 3 GenAI/Agentic AI projects in production, ensuring reliability, scalability, and performance
- Integrate SQL, No-SQL, and vector databases such as Postgres, MongoDB, and ChromaDB
- Implement graph databases such as Neo4j for knowledge graph-based use cases
- Provide technical leadership and mentorship to engineering teams
- Collaborate with cross-functional stakeholders to identify and deliver GenAI solutions across multiple business domains
- Ensure robustness, security, and compliance of deployed AI systems
- Stay current with trends in GenAI, deep learning, and orchestration frameworks
- Document and present technical solutions to technical and non-technical audiences
Requirements
What you’ll need- Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, AI/ML, or related field
- 3+ years of total professional experience in AI/ML, Data Science, or related fields
- 3+ years of hands-on experience in Python with strong software engineering practices
- At least 3 years of experience in AI/ML engineering, including 2+ years of hands-on experience in Generative AI /Agentic AI
- Hands-on experience with deep learning frameworks (PyTorch, TensorFlow)
- Expertise in large language models (LLMs), prompt engineering, and fine-tuning
- Proven track record of deploying at least 3 GenAI/Agentic AI projects into production
- Strong background in Data Science or Data Engineering, including data pipelines, ETL, and data modeling
- Practical knowledge of SQL, No-SQL, vector databases, and graph databases
- Familiarity with LangGraph, AutoGen, LangChain, or similar agentic AI frameworks
- Experience with multi-agent systems and orchestration of intelligent workflows
- Knowledge of MLOps practices (CI/CD, model monitoring, retraining pipelines)
- Contributions to open-source AI/ML projects or published research in generative AI
- Strong problem-solving skills and ability to thrive in fast-paced R&D environments
Benefits
Comp & perks- Hybrid work arrangement
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonAI/ML EngineeringGenerative AIPrompt EngineeringDeep LearningSQLNo-SQLGraph DatabasesMLOpsData Pipelines
Soft Skills
Technical LeadershipProblem-SolvingCollaboration
Tools & Technologies
LangGraphAutoGenLangChainPostgresMongoDBChromaDBNeo4jPyTorchTensorFlow
Industry Keywords
GenAIDeep LearningData ScienceData EngineeringETL