AI Engineering Manager_Machine Learning

• Posted 3 days ago • Updated 6 hours ago
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Job Details

Skills

  • Metrics
  • Performance Tuning
  • automation
  • Product Management
  • backend
  • Governance
  • API design
  • Workflows
  • data protection
  • Regulatory Compliance
  • Mentoring
  • Artificial Intelligence
  • Requirements Analysis
  • Systems Design
  • Business Process Improvement
  • Low Latency
  • Code Review
  • Prompt Engineering
  • Large Language Models
  • Safety Principles
  • Application Programming Interfaces (APIs)
  • Reliability
  • Technical Supervision
  • Open Source Technology
  • Software Debugging
  • Strategic Thinking
  • Decision Making Skills
  • Data Streaming
  • Team Working
  • Creating Prototypes
  • Access Controls
  • Execution of Experiments
  • Software Deployment
  • Monitoring of Systems
  • Knowledge of Statistics
  • Search Technologies
  • Intelligent Systems
  • Benchmarking Skills
  • Automated Storage and Retrieval Systems
  • Tool Management

Summary

Role: Sr AI Engineering Manager_Machine Learning

Experience: - Minimum 10+ Years

Location: - USA Remote

Hiring Type: - C2C Visa Independent

We are looking for a AI Engineer to design, build, and deploy high-quality AI-powered features with end-to-end ownership from prototyping to production, ensuring reliable, scalable, and impactful AI solutions.

Responsibilities: -

End-to-End AI Feature Ownership

  • Design and implement AI-powered features (LLM workflows, copilots, and agent-based systems with tool use and multi-step reasoning)
  • Own the Full Lifecycle: prototyping evaluation production deployment iteration
  • Ensure solutions are reliable, performant, and aligned with product needs

AI System Implementation

  • Build and optimize prompt pipelines for specific use cases
  • Build retrieval systems (embeddings, chunking, ranking)
  • Implement RAG-based workflows where needed
  • Iterate on outputs to improve quality, accuracy, and consistency
  • Design scalable and cost-efficient AI architectures for production workloads
  • Select and evaluate models (hosted vs open-source) based on use case constraints

Agent-Based Systems (AgentCore)

  • Design and build agentic workflows capable of multi-step reasoning and decision-making
  • Integrate agents with tools, APIs, and internal systems to perform real-world actions
  • Implement planning, execution, and reflection loops for complex tasks
  • Manage context, memory, and state across multi-step interactions
  • Balance deterministic workflows vs. agent autonomy for reliability and control

Experimentation & Evaluation

  • Run structured experiments to compare approaches (prompting, retrieval, models)
  • Define and track key metrics for AI performance (quality, latency, cost)
  • Debug and improve non-deterministic system behavior
  • Build and maintain evaluation datasets and benchmarks
  • Implement automated evaluation pipelines for continuous improvement

Collaboration & Contribution

  • Drive technical direction and influence AI adoption across teams
  • Partner with product managers and designers to scope AI features
  • Contribute to shared patterns and reusable components
  • Participate in code reviews and design discussions
  • Support and mentor mid-level engineers where needed

AI Reliability, Safety & Governance

  • Design guardrails to ensure safe and reliable AI behavior
  • Mitigate hallucinations, prompt injection, and model misuse
  • Ensure compliance with data privacy and enterprise requirements
  • Implement monitoring and observability for AI systems in production
  • Implement guardrails for agent actions (tool access control, execution boundaries)
  • Prevent failure cascades in multi-step agent

Educational Qualifications: -

  • Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
  • Technical certification in multiple technologies is desirable.

Skills: -

Mandatory skills

Core AI Skills

  • Strong understanding of LLM capabilities and limitations
  • Experience with prompt engineering and structured output design
  • Hands-on experience with embeddings and vector search
  • Familiarity with RAG architectures and when to apply them
  • Experience designing agent-based architectures (AgentCore concepts)
  • Understanding of tool use, planning strategies, and memory mechanisms in LLM systems

Engineering Skills

  • 5+ years of related work experience
  • Solid backend/system design fundamentals
  • Experience building and deploying production-grade systems
  • Ability to debug complex issues, including probabilistic outputs
  • Comfort working with APIs, pipelines, and data flows

Product Thinking

  • Ability to translate user needs into effective AI solutions
  • Strong intuition for balancing quality, latency, and cost
  • Focus on delivering measurable product impact

Collaboration

  • Communicates clearly across engineering and product teams
  • Contributes to team knowledge and shared practices.

Good to have skills

  • Evaluate agent performance across multi-step tasks (task success rate, error propagation)
  • Debug and optimize agent decision-making and tool selection behavior
VeeRteq Solutions is an Equal Opportunity Employer
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91122967
  • Position Id: 2026-4404
  • Posted 3 days ago

Company Info

About ADDSOURCE

AddSource is a premier staffing and workforce solutions partner headquartered  in  Delaware,  USA,  with  operations  in  Alberta,  Canada  under  the  brand  name AddSource.

We  specialize  in  connecting  top-tier  talent  with  leading organizations across diverse industry sectors.

With  a  strong  commitment  to  excellence,  our  mission  is  to deliver innovative, customized staffing solutions that empower clients  to  achieve  their  goals  while  helping  candidates advance their careers.

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