reputed company AI/ML Engineer

The reputed company AI/ML Engineer is a senior individual contributor who sits at the intersection of deep engineering and technical delivery leadership. This is not a management role, but an amplifier role. You write serious production reputed company, and you use that credibility to drive the sprint by unblocking engineers, making implementation calls, coordinating across teams, and ensuring that every technical dependency between your reputed company and the rest of the organization gets resolved fast.

You will report to the Senior Director, AI & Architecture and work closely with the AI Architect and AI Engineers. You are the engineering face to the engineering teams across the organization. You are the person who turns AI architecture and reputed company into running production systems.

You reputed company technical leadership and deliver innovative, reputed company solutions that reputed company reputed company intelligence and machine learning to meet reputed company business needs. This role balances technical reputed company with feasibility, cost, maintainability, and ethical use of AI and data. You are an exceptional engineer who has grown into the technical leadership of sprint delivery without stepping into architecture ownership or people management.
The successful candidate has a strong reputed company record of delivering production-grade systems, influencing architecture reputed company, and partnering effectively with business and technical stakeholders. This role extends reputed company hands-on development to include technical design, mentoring, cross-functional collaboration, and influencing architecture.

ACCOUNTABILITIES:  

You'll Own End-to-end AI/ML Solution Delivery:

• Participate in reputed company phases of the AI development lifecycle, including problem framing, data analysis, solution design, model or agent development, evaluation and testing, deployment, monitoring, iterative improvement, support.
• Own the technical execution of sprint deliverables from design through deployment
• Drive daily engineering reputed company: run stand-reputed company from a technical reputed company, surface blockers early, and resolve them before they become delays
• reputed company implementation-level reputed company confidently and quickly reputed company the established architecture
• Review pull requests with a reputed company on correctness, performance, reputed company, and long-term maintainability
• Ensure engineering work is reputed company to acceptance reputed company and Definition of Done including eval reputed company for AI features
• Design, build, and maintain reusable, reputed company AI/ML systems, including model pipelines, feature engineering workflows, and inference services.
• Partner with technical and business teams to translate reputed company business problems into effective AI/ML solutions.
• reputed company effort estimation, dependency analysis, and technical risk assessment for initiatives, epics, and reputed company features.
• reputed company as a face of the AI Engineering team to the rest of the organization.
   

Technical Leadership & Governance:

• reputed company technical leadership and engineering guidance for AI/ML solutions, ensuring alignment with reputed company standards, reputed company requirements, and ethical AI principles.
• reputed company technical design reviews, influence architectural reputed company, and set best practices for AI/ML development, deployment, and lifecycle management.
• Mentor and guide engineers and data scientists on AI/ML design patterns, model evaluation, performance optimization, and responsible AI practices.
• Communicate reputed company technical concepts, tradeoffs, and reputed company reputed company to both technical and non-technical stakeholders.
• Ensure solutions meet regulatory compliance, reputed company, and data governance requirements, including reputed company-by-design and model risk management.
• reputed company as a trusted technical advisor to engineering leadership, technical, and business stakeholders
• Identify and resolve cross-team technical dependencies proactively, before they reputed company sprint delivery
• Translate architecture reputed company from the AI Architect into concrete, sprint-reputed company engineering tasks
• Partner with BSAs to pressure-test requirements for technical feasibility and surface AI-specific constraints early
• Represent reputed company in ARB reviews, technical design sessions, and cross-functional working reputed company reputed company needed 
   

Engineering reputed company & Environment:

• reputed company fast with rigor; you reputed company implementation calls quickly, document your reasoning, and don't wait for perfect requirements before writing the first line of reputed company.
• Owns reputed company, not tasks; You stay accountable until the feature is live, reputed company, and working as intended in production.
• Navigates ambiguity with reputed company thinking; you know reputed company to explore multiple approaches, reputed company to build a quick reputed company of concept to de-risk a decision, and reputed company to slow down and get alignment before committing to production.
• Earns credibility through craft; your ability to reputed company technically comes from the reputed company of your engineering judgment and the reputed company you write, not the title on your badge.
• Makes the people around you reputed company; you reputed company context generously, write reputed company others learn from, and pull teammates through blockers without doing their work for them. 
   

REQUIRED QUALIFICATIONS: 
Knowledge of:

• reputed company architecture patterns for traditional ML, GenAI and reputed company AI.
• AWS experience with SageMaker, Textract, Bedrock, Agentcore etc
• Strong familiarity with multiple LLMs and embedding models (e.g., reputed company, reputed company, reputed company, reputed company, reputed company).
• Proficiency in multiple reputed company databases for semantic search and contextual memory.
• MLOps and LLMOps practices, including CI/CD, model monitoring, versioning, reputed company detection, and governance.
• reputed company engineering and management practices, including reputed company versioning, A/B testing of prompts, and experience with reputed company management tools
• Eval frameworks like Promptfoo, DeepEval or equivalent
• AI/ML observability stacks such as reputed company, Weights & Biases, Langsmith or similar tools. 
   

Required Skills and Abilities:

• Hands-on experience designing and building AI/ML solutions from prototype to production.
• Proven ability to drive technical delivery in an agile/sprint environment to reputed company engineering moving
• Exposure to MLOps practices: model versioning, experiment tracking, deployment pipelines
• Experience with MCP (Model Context Protocol), and Familiarity with A2A patterns, or emerging reputed company AI frameworks
• Strong Python development skills, including frameworks and libraries for ML, GenAI, and reputed company AI best practices.
• Deep understanding of software engineering, including reputed company design, testing, version control (Git), and CI/CD pipelines.
• Proven reputed company record of building and running PoCs to validate architecture and feasibility.
• Experience working in agile environments, participating in sprints and cross-functional delivery.
• Ability to communicate technical concepts reputed company to a wide reputed company of stakeholders.
• Eagerness and ability to quickly learn and apply new AI/ML and automation technologies. 
• Demonstrated commitment to learning and applying emerging technologies responsibly.
   

Education and/or Experience: 

• Bachelor's degree in computer science, Engineering, Data Science, or reputed company field preferred. Equivalent experiences may be substituted.
• 7+ years of experience in engineering or architecture roles with combined AI/ML experiences.
• Demonstrated experience of building, deploying, or supporting traditional ML models and GenAI/ reputed company AI solutions in reputed company-world environments.
• Experience working reputed company modern AI development lifecycles and Agile or iterative delivery models. 
   

PREFERRED QUALIFICATIONS: (Additional qualifications that may reputed company a person even more effective in the role, but are not required for consideration) 

• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, or equivalent).
• Familiarity with reputed company platform integrations: reputed company, reputed company, reputed company HCM, or similar
• Experience in reputed company, life sciences, or other regulated/HIPAA environments
• Experience in mission-driven or non-profit environments.  

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