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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and delivering GenAI solutions, including LLM/RAG, while effectively collaborating across engineering and data science teams. Proficient in Python/R, cloud platforms, and model deployment, with a strong focus on solution quality and stakeholder communication.
Highest-signal resume keywords
Python/R ProgrammingLLM/RAG ToolchainsCloud ML ExperienceData Remediation RequirementsModel Risk Controls
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonRPandasNumPyScikit-learnTensorFlowPyTorchSQLNLPTime Series Forecasting
Soft Skills
Analytical Problem-SolverClear CommunicatorCollaborativeSelf-DirectedOutcome-Oriented
Tools & Technologies
AWSGCPAzureDockerKubernetesPrometheusGrafanaTableauPower BIPinecone
Certifications & Qualifications
MScPhD
Industry Keywords
GenAIModel GovernanceData EngineeringFeature EngineeringBig DataCI/CDExperiment DesignOptimizationSimulationQuantitative Analytics
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformGrafanaKubernetesNoSQLNumpyPandasPrometheusPythonPyTorchScikit-LearnSQLTableauTensorflow
About the role
Key responsibilities & impact- Design and deliver GenAI solutions including LLM/RAG for enterprise use cases
- Develop retrieval strategies, embeddings, vector stores, prompt flows, and grounding approaches
- Evaluate and improve solution quality using offline and online quality, latency, and cost metrics
- Harden solutions for production through observability, monitoring, tracing, guardrails, safety controls, and reliability practices
- Build and integrate model endpoints into products and workflows through APIs and services
- Partner with engineering teams through deployment
- Work across Azure, AWS, and GCP cloud platforms, integrating storage, compute, orchestration, and model/runtime components
- Assess data readiness for modeling and RAG, including fitness, quality, and access
- Define data remediation requirements
- Collaborate in cross-functional data science, data engineering, engineering, and product squads
- Contribute to reusable assets and ways of working
- Communicate trade-offs, evaluation results, risks, and adoption actions to stakeholders
- Own end-to-end workstream delivery and lead stakeholder conversations
- Mentor others at more senior levels
- Shape solution direction and quality standards, coach teams, and contribute to sales pursuits, bids, and accelerators at the most senior levels
Requirements
What you’ll need- Strong Python/R, including pandas, NumPy, scikit-learn, TensorFlow, and PyTorch
- Experience with LLM/RAG toolchains such as LangChain, LlamaIndex, or Semantic Kernel
- Experience with vector search tools such as Pinecone, Weaviate, FAISS, or Azure AI Search
- Hands-on experience with AWS Bedrock and SageMaker highly desirable
- Experience with GenAI platforms such as OpenAI API, Anthropic, Gemini, or Llama
- Exposure to big data/distributed computing and pipeline/feature engineering
- Knowledge of LLM safety and governance, including hallucination mitigation, grounded responses, and audit trails
- Degree in a quantitative field
- Hands-on exposure to building models and setting up MLOps using Prometheus/Grafana or similar
- Cloud ML experience with AWS, GCP, or Azure preferred
- Strong SQL and experience with Tableau, Power BI, or Python visualization preferred
- Specialism in NLP, computer vision, or time series preferred
- NoSQL familiarity preferred
- Quant/trading analytics engineering practices preferred
- Experience with time-series forecasting preferred
- Experience with optimization/simulation preferred
- Knowledge of model risk controls preferred
- CI/CD, deployment, monitoring, Docker, or Kubernetes experience preferred
- Experiment design and randomized trials experience preferred
- MSc preferred; PhD a plus
- Analytical, pragmatic problem-solver; outcome-oriented
- Self-directed, able to prioritize and juggle multiple workstreams
- Clear communicator who can simplify complexity
- Collaborative, curious, continuous learner
Benefits
Comp & perks- Industry-leading compensation and benefits
- Top training and development opportunities
- Dedicated training and career paths
- Inclusive and entrepreneurial culture
- Global reach and opportunity to work with market-leading brands
- Opportunity to grow your career and achieve personal ambitions