Senior Technical Lead

Job description

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