Role Overview

We are looking for a Sr. DevOps Engineer to help build, operate, and continuously improve the secure cloud platforms that power Juvare’s mission-critical enterprise resilience solutions. In this role, you’ll partner across Engineering and Security to deliver reliable, scalable SaaS environments for commercial and federal customers, with a proven track record operating in regulated settings. Experience supporting AI/MLOps workflows is a plus.

Location

• Atlanta / Remote

Must Have

• Cloud Platforms: Strong hands-on experience with AWS and Azure
• Regulated Environments: Experience operating in FedRAMP High, DoD Impact Level 5 (IL5), or equivalent regulated environments
• Compliance & ConMon: Strong understanding of Authority to Operate (ATO) processes, compliance, and continuous monitoring (ConMon)
• GovCloud: Experience working within AWS GovCloud or secure boundary environments
• Databases: Operational experience with managed databases (backup/restore, replication, performance, and access management; Azure SQL and Aurora PostgreSQL preferred)
• Infrastructure as Code: Experience with infrastructure as code (Terraform)
• CI/CD Pipelines: CI/CD pipeline experience (GitLab, GitHub)
• Automation (AI-Enabled): Experience building workflow automation and developer automation using tools like n8n, Replit, or similar
• Containers & Orchestration: Strong experience with containers and orchestration (Docker, Kubernetes, AKS, EKS, ECS/Fargate)
• Monitoring & Observability: Experience with monitoring and observability (Datadog, CloudWatch)
• Security Tooling: Exposure to security tooling (WAF, SIEM, vulnerability management)
• Scripting: Strong scripting skills (Python, Bash, Powershell)
• Production Operations: Experience in production operations (incident response, on-call, RCA)
• Architecture: Strong understanding of networking, security, and system architecture
• AI / MLOps:
  • MLOps Pipelines: Experience with MLOps pipelines (training, deployment, monitoring)
  • Tools: Familiarity with tools like SageMaker, MLflow, Kubeflow, or similar
  • Model Deployment: Experience deploying models to production (real-time or batch)
  • Data & Lifecycle: Understanding of data pipelines and model lifecycle management

Nice to Have

• Experience with LLMs / GenAI workflows (RAG, prompt engineering, fine-tuning)
• Familiarity with vector databases (Pinecone, Weaviate, OpenSearch)
• Exposure to AIOps or AI-driven automation
• Experience with data platforms (Databricks, Snowflake, Redshift)
• GCP experience a plus; comfort operating with a cloud-agnostic mindset
• Multi-cloud or hybrid architecture experience
• Cost optimization and performance tuning
• Jira / Confluence experience

What We're Looking For

• Ownership Mindset: Strong sense of ownership in regulated, high-stakes environments — you treat the platform like it's yours
• Compliance + Speed: Ability to balance compliance, security, and delivery speed without sacrificing one for the other
• Cross-Team Collaboration: Comfortable working across SysOps, Engineering, and Security teams — you're a bridge, not a silo

Additional Information:

This position requires access to information that is controlled by the Export Administration Regulations (“EAR”).  A candidate must qualify as a “U.S. Person” or be otherwise eligible to access EAR covered materials through an EAR exception or license.  A "U.S. Person" as defined by the EAR includes a U.S. Citizen, U.S. national, lawful permanent resident, refugee, or asylee.

As the Company is a partner with the United States government, this position may require access to sensitive government information. Accordingly, candidates must be capable of passing an SF-85 background check and obtaining public trust clearance if required.

As a Senior ML Platform Engineer, you will contribute to building the ML platform at Prizepicks to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.

What you’ll do:

• Build Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, setup platform for transitioning experimental Data Science models into robust, high-availability production services.
• Real-Time Inference at Scale: Build automation for deploying low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Feature Engineering & Data Strategy: You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
• End-to-End MLOps: You will work with the Infrastructure team to build and operate core ML platform components for training and experimentation enablement considering developer experience. You will champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability for ML systems to ensure data drift and model degradation are caught and addressed instantly.

What you have:

• 5+ years of experience in Platform Engineering, with a proven track record of deploying and maintaining a scalable ML platform in high-traffic production environments. 
• 2+ years of experience owning ML systems end-to-end in production, including on-call and incident response.
• Experience with Real-Time Data, proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms.
• MLOps Expertise, deep experience building a platform for managing the full ML lifecycle (training, deploying, monitoring) using tools like SageMaker, VertexAI, Vector DBs, Graph Databases. Managing and scaling caches like Redis or Elasticsearch.  
• Proficient with Containerization, Docker, Kubernetes, and cluster-level management.
• Expert in Python, proficiency in Go. C++, or Rust is a strong plus for building high-performance inference layers.

What makes you stand out:

• Experience implementing infrastructure while enforcing best practices for the deployment of ML Platform. 
• Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
• Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.
• Enabling self-service for ML and Data Science teams for model development and deployment.
• Enabling AI agents and AI coding for faster and iterative software development.

Where you’ll live:

• While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote 

Working at PrizePicks:

The typical salary range for this position is $160,000 to $210,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process. 

This application period will remain open for 30 days. We’re committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.

Date Posted:  4/27/2026

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.

What you’ll do:

• Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services.
• Real-Time Inference at Scale: Steer the design and deployment of low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Feature Engineering & Data Strategy: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
• End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.

What you have:

• 7+ years of experience in Machine Learning Engineering or Backend Engineering, with a proven track record of deploying and maintaining complex ML models in high-traffic production environments.
• 3+ years of technical leadership, acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms.
• Experience with Real-Time Data: Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms.
• MLOps Expertise: Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, Databricks, or SageMaker.
• Strong Coding Skills: Expert in Python and SQL; proficiency in Go, C++, or Rust is a strong plus for building high-performance inference layers.
• Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents.

What makes you stand out:

• Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection.
• Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
• Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.

Where you’ll live:

• While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote 

Working at PrizePicks:

The typical salary range for this position is $220,000 to $280,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process. 

This application period will remain open for 30 days. We’re committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.

Date Posted: 4/16/2026

Method is a global design and engineering consultancy founded in 1999. We believe that innovation should be meaningful, beautiful and human. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams based in New York, Charlotte, Atlanta, London, Bengaluru, and remote work with a wide range of organizations in many industries, including Healthcare, Financial Services, Retail, Automotive, Aviation, and Professional Services.

Method is part of GlobalLogic, a digital product engineering company. GlobalLogic integrates experience design and complex engineering to help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses. GlobalLogic is a Hitachi Group Company.

We are seeking an experienced Principal Data Architect to join our Data & AI team. In this leadership role, you will help shape modern data and AI architecture strategies that enable organizations to achieve business outcomes through scalable, reliable, and secure data platforms. You will work closely with senior stakeholders, client teams, and engineering teams to define architectural direction, guide implementation approaches, and support the delivery of data-driven capabilities across analytics, AI, and operational use cases. You will exemplify Method culture and values by driving standards of excellence and mentoring and educating those who are accountable to you on projects or within the data engineering discipline. You will be reporting into the head of the Data & AI team. 

This role requires a strong blend of technical depth, architectural thinking, client engagement and team mentorship. You will be expected to navigate ambiguity, align business and technology priorities, and help teams deliver practical, high-quality solutions that support long-term value creation. In addition to shaping solution direction, you will play an important role in guiding and developing data engineering teams through coaching, knowledge sharing, and hands-on support.

Travel for team, client and sales meetings is required, typically up to 25%. This is a US-based position in the East Coast or Mid-Central time zone.

Job Responsibilities

• Lead complex data and AI platform initiatives, addressing architectural concerns while enabling delivery teams to meet defined standards, timelines, and budgets.
• Provide client-facing technical leadership on data architecture, data engineering, analytics platforms, and AI/ML infrastructure.
• Collaborate with enterprise architects and senior technology stakeholders to align on architectural decisions, trade-offs, and implementation approaches.
• Communicate architectural concepts clearly to both engineering teams and business stakeholders.
• Design architectures that bridge operational systems and analytical platforms, enabling data products, advanced analytics, and AI capabilities.
• Define and implement architectures for data governance, security, privacy, and regulatory compliance.
• Establish and integrate data quality frameworks, observability practices, and data reliability processes.
• Partner with sales and pre-sales teams to shape solution approaches, validate technical feasibility, and support proposals.
• Develop new value propositions and offerings for the data engineering at Method, create go to market strategies, test and refine the offerings during the sales pursuits.
• Grow and maintain the data engineering team. Provide career guidance and facilitate career development opportunities across Method. 
• Create an environment that brings together the best of various data disciplines with care for the uniqueness of each project. 
• Foster a culture of curiosity and learning, creating opportunities for employees to learn and grow into our future leaders.

Skills Required
Technical Skills

• 8+  years of experience in data engineering, with 3+ years in a technical leadership role. 
• Experience designing and implementing modern data architectures, including lakehouse, data mesh, and real-time data platforms, and evaluating technology trade-offs.
• Strong background in distributed systems and data-intensive applications.
• Experience building and operating large-scale data platforms, including data warehouses, streaming systems, and data lakes.
• Expertise in data modeling, data platform operations, observability, and reliability engineering for data systems.
• Proficiency with modern data and distributed technologies such as Spark, Kafka, Flink, Trino/Presto, Iceberg/Delta/Hudi, and distributed storage systems.
• Experience designing streaming and low-latency architectures and understanding their operational trade-offs.
• Experience designing and deploying AI/ML platforms, including feature stores, model training pipelines, and model serving systems.
• Familiarity with MLOps and ML productionization practices, including CI/CD, model monitoring, and governance.
• Strong experience working with cloud platforms (AWS, Azure, or GCP) and cloud-native data services.
• Experience with modern data platforms such as Snowflake, Databricks, or similar analytics environments.
• Understanding of data governance frameworks, data cataloging, lineage, and privacy controls.
• Experience implementing data-driven decision systems, advanced analytics, and machine learning solutions in enterprise environments.

Professional Skills

• Advise C-suite executives on data strategy, AI investment, and digital transformation at the highest organizational level.
• Strong experience supporting pre-sales, solution shaping, and technical discovery engagements.
• Support client partners in growing key accounts by identifying new opportunities, navigating complex situations, and educating clients on the value of our work beyond data and AI.
• Excellent stakeholder management skills and the ability to build trust with both business and technical leaders.
• Ability to cultivate strong partnerships across organizations to drive adoption of modern data and AI capabilities.
• Strong influencing skills, with the ability to galvanize, inspire, and align others around a shared direction.
• Contribute Thought Leadership through presentations, blogs, or public talks
• Strong conflict resolution and risk management skills.
• Team player with the capacity to mentor, guide, and champion engineering teams and architects.
• Commitment to technical excellence, pragmatic delivery, and continuous improvement. 

Why Method?

We look for individuals who are smart, kind and brave. Curious people with a natural ability to think on their feet, learn fast, and develop points-of-view for a constantly changing world find Method an exciting place to work. Our employees are excited to collaborate with dispersed and diverse teams that bring together the best in thinking and making. We champion the ability to listen, and believe that critique and dissonance lead to better outcomes. We believe everyone has the capacity to lead and look for proactive individuals who can take and give direction, lead by example, enjoy the making as much as they do the thinking, especially at senior and leadership levels.

We believe in work/life balance. Seriously. We offer a ton of competitive perks, including:

• Continuing education opportunities 
• Flexible PTO and work-from-home policies 
• Pension 
• Health and dental benefits
• Company lunches, company outings, along with a lot of snacks 
• Health and wellness programs 
• Other location specific perks (just ask!)

Next Steps

If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a portfolio, GitHub, Dribbble or other platform.

* For information on how we process your personal data please see Privacy.

* If you are a California resident, more details on how we process your personal information can be found in the CCPA Recruitment Privacy Notice (https://www.globallogic.com/privacy/ccpa-recruitment-privacy-notice/)"

Colorado Applicants (Colorado Equal Pay for Equal Work Act Disclosure):  The starting salary range for this role to be performed in Colorado is estimated to be between $160,000 to $200,000 annually.  This salary range is specific to Colorado residents only, and provided as a general estimate.  The amount offered may be higher or lower. Method  takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations. 

New York City Applicants (New York City Local Law 32;  Pay Transparency Law):  The starting salary range for this role to be performed in New York City is from $192,000 to $205,000. This salary range is specific to New York City residents only, and provided as a general, good faith estimate. The amount offered may be higher or lower. Method takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.

CSQ227R88

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ127R310

Candidates located anywhere within the Central or Eastern Time Zones are also eligible for consideration for this role.

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ127R318

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ227R87

Candidates located anywhere within the Central or Eastern Time Zones are also eligible for consideration for this role.

As a Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap hands-on projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Apache Spark™ runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Capable of design and deployment of highly performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Experience in building scalable streaming and batch solutions using cloud-native components
• Travel to customers up to 20% of the time
• Nice to have: Databricks Certification