MlOps Engineer / AI/ML Engineer - AWS / Plano, TX / W2 Only / Vishal

Job Role: MlOps Engineer /AI/ML Engineer - W2 Only

Location: Plano, Texas - Onsite

Interview Mode: In- Person Visa: & GC Considering Only Local to Texas

Required Experience: Min 14 Years
Note :Not considering OPT/CPT & No third-party

MUST have skills

• AI/ML knowledge (2-3 years)
• AWS 8 years
• observability tools - Grafana, Slunk, Dynatrace
• automation scripting languages - Bash, shell script, groovy

NICE to have skills

• programming language - java
• DEvOps skillset
• terraform

Key Responsibilities

• Design, develop, and deploy AI/ML models and agent-based systems that automate technology and platform workflows for the internal Deposits2.0 platform.
• Lead the integration of intelligent agents into operational processes to improve decision-making, workflow execution, and process optimization across engineering and operations.
• Build AI-assisted tooling that improves Infrastructure as Code (IaC) development, validation, and change management (examples: Terraform, Ansible, CloudFormation style patterns) across cloud and on-prem environments.
• Partner with DevOps and platform engineering teams to enhance CI/CD pipelines using AI/ML for signal detection, predictive analytics, and automated remediation.
• Develop AI-powered observability automation to monitor, analyze, and proactively manage application and infrastructure health for internal platform services.
• Automate alert triage, root cause analysis assistance, and incident response workflows using ML-driven techniques, with clear guardrails and measurable outcomes.
• Engineer or enable data pipelines and feature workflows needed to support model training, evaluation, and real-time or near-real-time inference use cases.
• Implement and operate MLOps capabilities (deployment patterns, monitoring, quality gates, rollback strategies, documentation) aligned to enterprise expectations for reliability and risk management.
• Collaborate with cross-functional teams (engineering, product, SRE, operations, architecture, controls) to identify high-value automation opportunities and deliver outcomes that can be adopted at scale.
• Continuously evaluate emerging AI/ML approaches and tooling, and translate them into practical, secure, and maintainable platform capabilities.

Required Qualifications (Minimum)

• Bachelor s or Master s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 14+ years total engineering experience with 8+ years hands-on experience delivering AI/ML engineering solutions in production environments.
• Strong programming skills in Python; Java experience is a plus, especially for enterprise platform integration.
• Experience with ML frameworks such as PyTorch, TensorFlow, and scikit-learn, including model training and evaluation workflows.
• Hands-on experience building agent-based systems and integrating them into real operational or engineering workflows.
• Experience applying AI/ML to automate or improve Infrastructure as Code workflows (examples: generation assistance, validation, policy checks, drift detection, change risk scoring).
• Familiarity with observability fundamentals and toolsets (examples: Prometheus, Grafana, ELK stack) and experience automating operational workflows using AI/ML.
• Strong foundations in data structures, algorithms, machine learning, statistics, and software engineering best practices.
• Experience integrating AI capabilities into modern software development practices and supporting legacy modernization or code transformation initiatives.
• Strong communication and collaboration skills, with the ability to work effectively across engineering and operations stakeholders.