What are the responsibilities and job description for the Senior Agentic AI Developer position at Shrive Technologies?
Required Qualifications
Experience: Minimum 8 years of professional software engineering experience with a proven track record in full-stack or backend development.
Core Technical Stack: Deep practical knowledge of Java and Python, demonstrated through significant development experience.
Generative AI Expertise: Hands-on experience with LLMs, specifically the Gemini family , and their application in agentic workflows, reasoning tasks, and tool-calling.
Agentic Frameworks: Familiarity with Agent Development Kit (ADK), Model Context Protocol (MCP), and agent design in Vertex AI.
Cloud Infrastructure: Strong understanding of cloud-native development on GCP
Leadership: Demonstrated ability to lead complex projects from requirement gathering to production release, acting as a strategic liaison between engineering and product stakeholders.
Addition Skills (Good to Have)
Experience in Google-proprietary technologies such as Borg, Blaze, Piper, and Critique.
Cloud-native development on GCP, including experience with Spanner, BigQuery, and Pub/Sub.
Key Responsibilities
Agentic Workflow Design: Architect and orchestrate autonomous agents capable of planning, executing, and verifying complex engineering tasks such as code generation, unit test case creation, and automated bug triaging.
Platform Integration: Develop and maintain Model Context Protocol (MCP) servers to connect agents to canonical internal documentation and tools, ensuring high-fidelity, grounded responses.
Tooling & Automation: Utilize the Google Antigravity platform and Agent Development Kit (ADK) to build context-aware assistants that integrate with existing IDEs and development tools.
Productionization: Lead the transition of AI Proof-of-Concept (POC) projects into production-ready services, collaborating with Moma and other internal search and productivity teams.
Architectural Leadership: Propose and implement architectural changes to agentic systems to improve reasoning capabilities, reduce latency, and optimize token usage.
Technical Mentorship: Guide junior engineers in adopting "vibe coding" practices and leveraging Gemini-powered agentic tools for effective software development.
Experience: Minimum 8 years of professional software engineering experience with a proven track record in full-stack or backend development.
Core Technical Stack: Deep practical knowledge of Java and Python, demonstrated through significant development experience.
Generative AI Expertise: Hands-on experience with LLMs, specifically the Gemini family , and their application in agentic workflows, reasoning tasks, and tool-calling.
Agentic Frameworks: Familiarity with Agent Development Kit (ADK), Model Context Protocol (MCP), and agent design in Vertex AI.
Cloud Infrastructure: Strong understanding of cloud-native development on GCP
Leadership: Demonstrated ability to lead complex projects from requirement gathering to production release, acting as a strategic liaison between engineering and product stakeholders.
Addition Skills (Good to Have)
Experience in Google-proprietary technologies such as Borg, Blaze, Piper, and Critique.
Cloud-native development on GCP, including experience with Spanner, BigQuery, and Pub/Sub.
Key Responsibilities
Agentic Workflow Design: Architect and orchestrate autonomous agents capable of planning, executing, and verifying complex engineering tasks such as code generation, unit test case creation, and automated bug triaging.
Platform Integration: Develop and maintain Model Context Protocol (MCP) servers to connect agents to canonical internal documentation and tools, ensuring high-fidelity, grounded responses.
Tooling & Automation: Utilize the Google Antigravity platform and Agent Development Kit (ADK) to build context-aware assistants that integrate with existing IDEs and development tools.
Productionization: Lead the transition of AI Proof-of-Concept (POC) projects into production-ready services, collaborating with Moma and other internal search and productivity teams.
Architectural Leadership: Propose and implement architectural changes to agentic systems to improve reasoning capabilities, reduce latency, and optimize token usage.
Technical Mentorship: Guide junior engineers in adopting "vibe coding" practices and leveraging Gemini-powered agentic tools for effective software development.