Tredence Inc.
Website:
tredence.com
Job details:
Role description
Role & responsibilities
Job Summary:
Seeking a Technical Lead with a strong combination of Technical Program Management (TPM) and hands-on engineering expertise. The role involves leading GenAI solution development, owning end-to-end architecture, and driving Agile delivery while actively contributing to Python-based AI systems, RAG pipelines, and production deployments.
Key Responsibilities (89 Points):
- Lead end-to-end delivery of GenAI solutions combining TPM oversight with hands-on technical contribution.
- Design and develop scalable Python-based applications and automation frameworks.
- Architect and implement RAG pipelines, prompt workflows, and agent-based systems using LangChain/LangGraph or similar frameworks.
- Own APIs, orchestration layers, evaluation frameworks, and monitoring systems.
- Define and implement LLM evaluation metrics (accuracy, hallucination detection, groundedness, bias checks).
- Build data validation, reconciliation, and quality frameworks using Python and SQL.
- Integrate AI workflows into CI/CD pipelines (AWS CodePipeline, Jenkins, GitHub Actions).
- Drive Agile/Scrum ceremonies including sprint planning, backlog grooming, and stakeholder updates.
- Ensure scalable cloud deployment on AWS using Docker/Kubernetes.
Must-Have Skills:
- 12+ years overall experience with strong techno-functional leadership exposure.
- 8+ years of hands-on Python development experience in production systems.
- 2+ years of experience working on GenAI/LLM-based applications (RAG, agents, prompts).
- Strong understanding of LLM evaluation, observability, and monitoring frameworks.
- Experience working in Agile/Scrum delivery models.
- Ability to manage stakeholders and translate business requirements into scalable technical solutions.
- Strong hands-on experience with AWS services (EC2, S3, Lambda, EKS, CloudWatch, etc.).
Nice to Have:
- AWS Certified Solutions Architect ProfessionalTechnical Lead with a strong combination of Technical Program Management (TPM) and hands-on engineering expertise. The role involves leading GenAI solution development, owning end-to-end architecture, and driving Agile delivery while actively contributing to Python-based AI systems, RAG pipelines, and production deployments.
Key Responsibilities (89 Points):
- Lead end-to-end delivery of GenAI solutions combining TPM oversight with hands-on technical contribution.
- Design and develop scalable Python-based applications and automation frameworks.
- Architect and implement RAG pipelines, prompt workflows, and agent-based systems using LangChain/LangGraph or similar frameworks.
- Own APIs, orchestration layers, evaluation frameworks, and monitoring systems.
- Define and implement LLM evaluation metrics (accuracy, hallucination detection, groundedness, bias checks).
- Build data validation, reconciliation, and quality frameworks using Python and SQL.
- Integrate AI workflows into CI/CD pipelines (AWS CodePipeline, Jenkins, GitHub Actions).
- Drive Agile/Scrum ceremonies including sprint planning, backlog grooming, and stakeholder updates.
- Ensure scalable cloud deployment on AWS using Docker/Kubernetes.
Must-Have Skills:
- 12+ years overall experience with strong techno-functional leadership exposure.
- 8+ years of hands-on Python development experience in production systems.
- 2+ years of experience working on GenAI/LLM-based applications (RAG, agents, prompts).
- Strong understanding of LLM evaluation, observability, and monitoring frameworks.
- Experience working in Agile/Scrum delivery models.
- Ability to manage stakeholders and translate business requirements into scalable technical solutions.
- Strong hands-on experience with AWS services (EC2, S3, Lambda, EKS, CloudWatch, etc.).
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