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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and deploying scalable AI systems, with a strong focus on real-time evaluation and observability. Proficient in developing interactive AI user interfaces and mentoring software engineers while collaborating across diverse teams.
Highest-signal resume keywords
Architecting AI/ML SystemsExpert Proficiency In PythonMulti-Agent Frameworks ExpertiseVector Databases ExperienceMLOps Framework Familiarity
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software Development ExperienceAI System DeploymentReal-Time AI EvaluationInteractive AI User InterfacesTool-Calling ParadigmsEvaluating LLMsAI Frontend DevelopmentModern React Concepts
Soft Skills
Strategic Problem-SolvingCollaborative ApproachHigh Accountability
Tools & Technologies
StreamlitChainlitLangGraphCrewAIADKN8nPineconeWeaviateMLflowKubeflow
Industry Keywords
MLOpsMulti-Cloud EnvironmentsRegulatory Compliance Standards
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformPythonReact
About the role
Key responsibilities & impact- Lead the architectural design and deployment of scalable, resilient autonomous AI systems and multi-agent decision engines
- Engineer and maintain high-throughput vector retrieval pipelines for RAG and semantic search
- Establish real-time AI evaluation and observability pipelines to monitor model health, latency, drift, and bias
- Develop interactive AI user interfaces using Streamlit, Chainlit, and React concepts
- Integrate safety guardrails, MCP integrations, structured function calling, and regulatory compliance standards
- Establish foundational AI engineering patterns
- Mentor junior and mid-level software engineers
- Collaborate across MLOps, cloud, and product teams
Requirements
What you’ll need- 5+ years of professional software development experience
- 2–3 years dedicated directly to architecting and deploying production AI/ML systems and agentic workflows
- Expert proficiency in Python
- Expertise with multi-agent frameworks including LangGraph, CrewAI, ADK, and n8n
- Expertise with vector databases including Pinecone and Weaviate
- Experience with tool-calling paradigms
- Hands-on experience evaluating and monitoring LLMs using LangSmith, AgentOps, or Langtrace
- Familiarity with MLOps frameworks including MLflow and Kubeflow
- Familiarity with multi-cloud environments including AWS, GCP, and Azure
- Proven capability building AI frontends using Streamlit or Chainlit
- Solid baseline understanding of modern React concepts
- High accountability, strategic problem-solving skills, and a collaborative approach
- Advanced English fluency, written and spoken, is mandatory
Benefits
Comp & perks- Continuous multi-project pipeline
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- L1-L7 Career Framework
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety
- Holidays off
- Paid time off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks