Senior Specialist - Product Engineering

LTM

$100K — $130K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in DevOps engineering
  • Strong expertise in automation and orchestration tools
  • Proficient in cloud and platform engineering practices
  • Familiarity with AI/ML or GenAI in engineering workflows
  • Experience in performance engineering and scalability design
  • Knowledge of failover and disaster recovery mechanisms
  • Deep understanding of the modern software delivery lifecycle

Responsibilities

  • Drive the transformation of DevOps practices using AI
  • Implement automation-first engineering methodologies
  • Lead initiatives for AI rollout in engineering workflows
  • Enable environments for AI experimentation and adoption
  • Establish frameworks for assessing engineering maturity
  • Build and enhance capabilities in resilience engineering
  • Implement frameworks for continuous optimization and monitoring

Benefits

  • Opportunity to significantly impact DevOps transformation initiatives
  • Engage in cutting-edge AI enablement in engineering
  • Work in a collaborative, client-facing role
  • Access to continuous learning opportunities in AI
  • Involvement in cross-functional teams focused on diverse technological areas
Full Job Description
Role description

Job Description:

Highly capable Onshore Engineers to join engagement teams focused on Platform Engineering Observability AI Enablement and DevOps transformation The roles require strong technical depth proactive ownership and the ability to operate in a highly collaborative client facing environment.

Required Skills Experience

Strong experience in DevOps engineering and CICD pipelines.

Expertise in

o Automation and orchestration tools.

o Cloud and platform engineering practices.

Exposure to AIML or GenAI enablement in engineering workflows.

Experience in

o Performance engineering.

o Scalability and resilience design.

o Failover and disaster recovery mechanisms.

Strong understanding of modern software delivery lifecycle

Key Responsibilities:

Drive DevOps transformation with AI enablement

Implement automation first engineering practices

Lead AI rollout initiatives across engineering workflows

Enable sandboxing environments for AI experimentation and adoption

Establish continuous assessment frameworks for engineering maturity

Build and enhance resilience engineering capabilities including

o Failover design and implementation

o High availability architecture

Drive performance engineering and scalability improvements

Implement continuous optimization and monitoring frameworks

Common Expectations

Operate in a high collaboration client facing environment

Demonstrate continuous learning mindset especially in AI adoption

Ability to work across cross functional teams Dev Ops Platform AI

Focus on

o Automation first delivery

o AI native engineering practices

o Operational excellence and reliability

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