Technical Lead

Job Summary

TECHNICAL JOB DESCRIPTION
• Use AI/ML pipeline security, adversarial ML defense model theft, prompt injection, and GCP AI infrastructure security Vertex AI to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope.
• Use GKE to design, provision, configure, migrate, and tune platform components using the required scope, supported by GCP security posture review and enterprise cloud security architect.
• Use data poisoning to implement, harden, test, and remediate security and access controls using the required scope, supported by IAM, VPC Service Controls, Cloud DLP, Cloud Armor. 
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Ensure adherence to secure coding, data handling, and access-control practices relevant to the platforms used in this demand.
• Collaborate with architects and peer engineers to validate design choices and technical trade-offs for the above tools.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Follow approved designs and engineering standards while using the above tools on assigned tasks.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Support stakeholder discussions, clarify assigned requirements, and escalate risks early.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 2 to 4 years of relevant industry experience aligned to the Junior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.

Key Responsibilities

TECHNICAL JOB DESCRIPTION
• Use AI/ML pipeline security, adversarial ML defense model theft, prompt injection, and GCP AI infrastructure security Vertex AI to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope.
• Use GKE to design, provision, configure, migrate, and tune platform components using the required scope, supported by GCP security posture review and enterprise cloud security architect.
• Use data poisoning to implement, harden, test, and remediate security and access controls using the required scope, supported by IAM, VPC Service Controls, Cloud DLP, Cloud Armor. 
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Ensure adherence to secure coding, data handling, and access-control practices relevant to the platforms used in this demand.
• Collaborate with architects and peer engineers to validate design choices and technical trade-offs for the above tools.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Follow approved designs and engineering standards while using the above tools on assigned tasks.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Support stakeholder discussions, clarify assigned requirements, and escalate risks early.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 2 to 4 years of relevant industry experience aligned to the Junior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.

Skill Requirements

AI/ML pipeline security, adversarial ML defense (model theft, prompt injection, data poisoning), and GCP AI infrastructure security (Vertex AI, GKE).

Secondary skills:

GCP security posture review and enterprise cloud security architecture (Security Command Center, IAM, VPC Service Controls, Cloud DLP, Cloud Armor)

TECHNICAL JOB DESCRIPTION
• Use AI/ML pipeline security, adversarial ML defense model theft, prompt injection, and GCP AI infrastructure security Vertex AI to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope.
• Use GKE to design, provision, configure, migrate, and tune platform components using the required scope, supported by GCP security posture review and enterprise cloud security architect.
• Use data poisoning to implement, harden, test, and remediate security and access controls using the required scope, supported by IAM, VPC Service Controls, Cloud DLP, Cloud Armor. 
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Ensure adherence to secure coding, data handling, and access-control practices relevant to the platforms used in this demand.
• Collaborate with architects and peer engineers to validate design choices and technical trade-offs for the above tools.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Follow approved designs and engineering standards while using the above tools on assigned tasks.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Support stakeholder discussions, clarify assigned requirements, and escalate risks early.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 2 to 4 years of relevant industry experience aligned to the Junior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.

Other Requirements

TECHNICAL JOB DESCRIPTION
• Use AI/ML pipeline security, adversarial ML defense model theft, prompt injection, and GCP AI infrastructure security Vertex AI to design, develop, evaluate, and operationalize AI/agentic capabilities using the required scope.
• Use GKE to design, provision, configure, migrate, and tune platform components using the required scope, supported by GCP security posture review and enterprise cloud security architect.
• Use data poisoning to implement, harden, test, and remediate security and access controls using the required scope, supported by IAM, VPC Service Controls, Cloud DLP, Cloud Armor. 
• Apply sound software engineering, configuration, and quality practices aligned to organizational standards for the above scope.
• Ensure adherence to secure coding, data handling, and access-control practices relevant to the platforms used in this demand.
• Collaborate with architects and peer engineers to validate design choices and technical trade-offs for the above tools.
• Demonstrate strong analytical, debugging, and problem-solving skills across the above tools and platforms.
• Maintain current proficiency, certifications, or hands-on practice on the primary tools listed for this role.
• Follow approved designs and engineering standards while using the above tools on assigned tasks.
FUNCTIONAL JOB DESCRIPTION
• Analyze and validate AI/ML use cases, agent workflows, evaluation criteria, and responsible-AI expectations.
• Translate stakeholder needs into functional requirements, user stories, acceptance criteria, and traceable deliverables.
• Facilitate requirement reviews, solution walkthroughs, demonstrations, UAT coordination, and business sign-off.
• Maintain functional specifications, process flows, decisions, risks, dependencies, and status reporting.
• Support stakeholder discussions, clarify assigned requirements, and escalate risks early.
• Support release readiness, user enablement, knowledge transfer, and post-go-live stabilization.
• Demonstrate strong verbal and written communication skills to engage client stakeholders, business users, and cross-functional delivery teams.
• Bring approximately 2 to 4 years of relevant industry experience aligned to the Junior Engineer band, with a track record of delivery in similar engagements.
• Apply working knowledge of AI domain standards, compliance expectations, and business processes relevant to this engagement.