FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and delivering complex AI systems, with a strong focus on secure integrations, architectural standards, and governance practices. Proven ability to mentor engineers and lead cross-functional collaboration to ensure high-quality AI solutions.
Highest-signal resume keywords
AI System DesignAWS AI ServicesAgentic AI SystemsAI Governance StandardsCloud Engineering
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI/ML Solution DevelopmentMulti-Agent ArchitecturesRAG ArchitecturesLLM Fine-TuningVector SearchIntegration PatternsInfrastructure as CodeCI/CDCost GovernanceObservability Frameworks
Soft Skills
CommunicationStakeholder ManagementMentoringCross-Functional CollaborationTechnical Influence
Tools & Technologies
SnowflakeAWS SageMakerAWS BedrockOpenSearchLangGraphAutoGenPgvectorDynamic TablesFeature PipelinesContainers
Industry Keywords
Artificial IntelligenceSoftware EngineeringData ScienceAI GovernanceProduction Systems
Tech Stack
Tools & technologiesAWSCloud
About the role
Key responsibilities & impact- Lead the technical design and delivery of complex, multi-component AI systems across our enterprise data platform.
- Define architectural patterns and engineering standards for AI development — RAG, agents, LLM integrations, and MCP-based enterprise connectivity.
- Drive secure, scalable integrations between AI models and enterprise data systems including Snowflake, AWS (SageMaker, Bedrock, S3), and ThoughtSpot.
- Own end-to-end AI solution quality — including evaluation frameworks, monitoring pipelines, cost governance, and production reliability.
- Lead cross-functional collaboration with data engineers, platform architects, and business stakeholders to shape requirements and validate solutions.
- Mentor and coach junior and mid-level engineers, conducting substantive code reviews and contributing to team technical growth.
- Champion AI governance standards — security, data access, PII, prompt injection, and responsible deployment practices.
- Proactively identify and resolve technical risks and architectural gaps; communicate escalations clearly to engineering leadership.
- Contribute to hiring processes — interviewing candidates and helping define role expectations.
- Lead knowledge-sharing sessions and represent the team in technical discussions with senior stakeholders.
Requirements
What you’ll need- Bachelor's degree or higher in Artificial Intelligence, Computer Science, Data Science, Software Engineering, or a related technical field (or equivalent practical experience).
- At least 4 years of professional experience in software engineering or AI engineering, including at least 2–3 years designing, developing, and deploying AI/ML solutions in production environments.
- Strong expertise in agentic AI systems, including multi-agent architectures, orchestration frameworks (e.g., LangGraph, AutoGen), and state management.
- Experience designing secure enterprise AI integrations using MCP or similar integration patterns.
- Advanced knowledge of vector search and RAG architectures using OpenSearch (kNN, hybrid search) and pgvector.
- Hands-on experience with LLM fine-tuning (LoRA, PEFT, RLHF) and selecting appropriate approaches across fine-tuning, prompt engineering, and RAG.
- Advanced experience with AWS AI services (including SageMaker and Bedrock) and Snowflake (Snowpark, Dynamic Tables, feature pipelines) for scalable AI solutions.
- Experience implementing AI evaluation, observability, security, governance, and compliance frameworks for production systems.
- Strong cloud engineering skills, including containers, Infrastructure as Code (IaC), CI/CD, and cost-optimized deployments.
- Excellent communication, stakeholder management, and mentoring skills, with the ability to influence technical decisions across cross-functional teams.
Benefits
Comp & perks- Private medical care
- Life insurance
- Employee Capital Plans (PPK)
- Paid vacation
- Paid sick leave
- Flexible working arrangements through a hybrid work model
- Access to professional development programs
- Access to sports and wellness programs
- Well-being initiatives
- Team-building events