5–10 years of Software Engineering experience with strong Python development (2+ years)
Hands-on experience with Generative AI frameworks (LangChain, ADK, agent-based architectures)
Strong understanding of SDLC and ability to design, build, and deploy scalable applications
Plusses:
Experience with MLOps / LLMOps and deploying AI models in production
Experience with multi-cloud platforms (Azure, GCP, OpenShift)
Background in DevOps (CI/CD, infrastructure as code)
Financial services or regulated industry experience
Cybersecurity awareness and safe AI development practices
Job Summary:
In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Software Engineering. Review and analyze complex multi-faceted, larger scale or longer-term Software Engineering challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel.
Day-to-Day Responsibilities:
Design and develop generative AI applications leveraging LLMs and enterprise data
Build agent-based AI solutions using frameworks such as LangChain and Agent Development Kit (ADK)
Develop Python-based services and applications supporting AI initiatives
Implement retrieval-augmented generation (RAG) pipelines and intelligent workflows
Collaborate with architects and engineers to align with enterprise technology strategies
Support cloud-native development and application deployment across Azure, GCP, and OpenShift
Contribute to MLOps/LLMOps practices including model deployment, monitoring, and scaling
Identify and resolve technical issues across development, build, and deployment pipelines
Participate in peer code reviews and enforce engineering best practices
Build prototypes and demos of AI solutions for internal business stakeholders
Work in Agile development environments with version control and branching strategies
Ensure security, scalability, and compliance of AI-enabled applications
Influence technical roadmaps and contribute to innovation initiatives across the organization