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data platform engineer (python) Jobs in New York

data platform engineer (python)

platform engineer

Smarsh

<div><div><b>Who are we?</b></div><div></div><div><br>
Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.</div><div></div><div><br>
The Platform Engineer will be a key member of the S&amp;E (Site &amp; Engineering) team, responsible for designing, building, and maintaining cloud infrastructure and platform services. This role focuses on enabling reliable, scalable, and secure platform operations while supporting oncall rotations and ensuring system availability across global operations.</div>
<h3 class="jobSectionHeader"><b>How will you contribute?</b></h3><div>
Bachelor&rsquo;s degree in Computer Science, Information Technology, or related field, or equivalent practical experience.</div>
<div>Minimum 4 years of experience in platform engineering, DevOps, or SRE roles.</div>
<div>Strong proficiency with AWS services including EC2, EKS, VPC, IAM, S3, RDS, Lambda, and CloudWatch.</div>
<div>Hands-on experience with Kubernetes administration and troubleshooting.</div>
<div>Proficiency in Terraform for infrastructure provisioning and management.</div>
<div>Experience with Istio or similar service mesh technologies.</div>
<div>Working knowledge of GitOps tools such as ArgoCD or Flux.</div>
<div>Experience with CI/CD tools including GitHub Actions, Jenkins, or GitLab CI.</div>
<div>Familiarity with HashiCorp Vault for secrets management.</div>
<div>Scripting proficiency in Python, Bash, or Go.</div>
<div><h3 class="jobSectionHeader"><b>Soft Skills</b></h3>
<div><div>Strong problem-solving and analytical abilities.</div>
<div>Excellent written and verbal communication skills.</div>
<div>Ability to work effectively in a distributed, global team environment.</div>
<div>Self-motivated with ability to work independently and as part of a team.</div>
<div>Willingness to participate in oncall rotations and respond to incidents.</div>
</div></div><h3 class="jobSectionHeader"><b>What will you bring?</b></h3><ul>
<li>4+ years of professional experience in platform engineering, DevOps, or Site Reliability Engineering roles.</li>
<li>Demonstrated hands-on experience managing production AWS environments at scale.</li>
<li>Proven track record of Kubernetes cluster administration and troubleshooting.</li>
<li>Experience implementing and maintaining Terraform-based infrastructure.</li>
<li>Background in CI/CD pipeline development and release engineering processes.</li>
<li>Prior oncall experience with demonstrated incident response capabilities.</li>
<li>Experience working in distributed, global team environments.</li>
</ul><h3 class="jobSectionHeader"><b>Preferred Qualifications</b></h3><ul>
<li>AWS certifications (Solutions Architect, DevOps Engineer, or equivalent).</li>
<li>Experience with observability tools such as Datadog, Prometheus, or Grafana.</li>
<li>Knowledge of incident management and RCA processes.</li>
<li>Experience with multi-region or multi-account AWS architectures.</li>
<li>Familiarity with compliance frameworks relevant to enterprise environments.</li>
</ul><h3 class="jobSectionHeader"><b>What do we offer?</b></h3><ul>
<li>Healthcare insurance: We provide medical, dental, and vision insurance, and a flexible spending account that allows you to set aside pre-tax dollars to pay for eligible out-of-pocket expenses.</li>
<li>Stock options.</li>
<li>Personal time off: A healthy work-life balance is critical to your success at the office. Smarsh offers a &ldquo;take-what-you-need&rdquo; time off policy as well as flexible work arrangements.</li>
<li>401K Match: Smarsh provides a 4% 401K match for which employees are fully vested on day one.</li>
<li>Sabbatical: The Smarsh sabbatical programme provides a time to recharge, study or simply do something you are passionate about away from the workplace. Employees are eligible after six years of service.</li>
<li>Recognition: We&rsquo;re big on kudos for a job well done. Our employee-recognition programme enables co-workers to nominate their peers who best embody our core values for recognition.</li>
</ul><div><div>The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.</div>
<div></div>
<div>The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.</div>
<div></div>
<div>Local cost of living assessments are done for each new hire at the time of offer.</div>
<div></div>
</div><div>Don't meet every requirement? Apply anyway! We value diverse candidates and encourage applications, even if you don't perfectly match the job description. Studies have shown that some strong candidates may self-select out of the interview process prematurely, at Smarsh we encourage an inclusive, high-performing environment.</div>
<div></div>
<div>Smarsh is an equal opportunity and affirmative action employer. Qualified applicants will receive consideration without regard to their race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Smarsh invites all qualified interested applicants to apply for career opportunities. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions. Including frequency of functions</div><div></div><div><b><br>
About our culture</b></div><div></div><div><br>
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world&rsquo;s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.</div></div>

Sr. Platform Engineer I

Alignerr

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 What if your Python expertise could directly shape the infrastructure powering next-generation AI? We're looking for a Senior Python Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve their models.
 <br/>
 <br/>
 This is a fully remote contract role working on real production systems &mdash; not toy projects. You'll be embedded alongside data, research, and engineering teams doing meaningful, high-visibility work at the frontier of AI development.
 <br/>
 <br/>
 <ul>
  <li>
   Organization: Alignerr
  </li>
  <li>
   Type: Hourly Contract
  </li>
  <li>
   Location: Remote
  </li>
  <li>
   Commitment: 20&ndash;40 hours/week
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and optimize high-performance Python systems supporting large-scale AI data pipelines and evaluation workflows
  </li>
  <li>
   Develop full-stack tooling and backend services for data annotation, validation, and quality control
  </li>
  <li>
   Identify and fix bottlenecks, edge cases, and reliability issues across production Python codebases
  </li>
  <li>
   Collaborate directly with data, research, and engineering teams to support model training and benchmarking
  </li>
  <li>
   Participate in synchronous design reviews to iterate on architecture and implementation decisions
  </li>
  <li>
   Improve performance, safety, and scalability across existing infrastructure
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Native or fluent English speaker with clear written and verbal communication skills
  </li>
  <li>
   5+ years of professional experience writing production-grade Python for data engineering
  </li>
  <li>
   Strong full-stack developer background with solid systems programming fundamentals
  </li>
  <li>
   Proficient with workflow orchestration tools for managing complex dependency graphs
  </li>
  <li>
   Experienced with dataframe processing libraries and cloud data warehouse SDKs
  </li>
  <li>
   Able to commit reliably to 20&ndash;40 hours per week
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Prior experience with data annotation, data quality pipelines, or evaluation systems
  </li>
  <li>
   Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
  </li>
  <li>
   Experience with distributed systems or developer tooling
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work on cutting-edge AI projects alongside leading research labs at the frontier of the field
  </li>
  <li>
   Fully remote and flexible &mdash; work from wherever you do your best thinking
  </li>
  <li>
   Freelance autonomy with the structure and consistency of meaningful, ongoing technical work
  </li>
  <li>
   Make a direct, tangible impact on the systems that shape how AI models learn and improve
  </li>
  <li>
   Potential for extended engagement and expanded scope as projects evolve
  </li>
 </ul>
</div>


Data Platform Engineer (Python)

Techfellow Limited

<div>
 <p>
  <strong>
   [Up to c. $450k Comp Package | Office-Led Working]
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Role Overview
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We&rsquo;re partnering with a top-tier, technology-led trading firm where machine learning plays a central role in decision-making and execution. This hire will sit within a highly specialised ML group, contributing to the design and evolution of the firm&rsquo;s research and production ML ecosystem. This is a hands-on engineering role operating close to research. You&rsquo;ll help build the systems, tooling, and infrastructure that enable rapid experimentation and efficient deployment of models - while also contributing to how machine learning is applied across a fast-moving, data-rich environment...
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Design and develop infrastructure supporting model training, evaluation, and production deployment
  </li>
  <li>
   Improve research workflows to accelerate iteration speed and feedback loops for ML experimentation
  </li>
  <li>
   Build clean, scalable tooling and APIs that make ML systems intuitive and efficient to use
  </li>
  <li>
   Collaborate with researchers to translate theoretical models into robust, production-ready solutions
  </li>
  <li>
   Evaluate and apply a broad range of modelling techniques depending on the problem space
  </li>
  <li>
   Maintain high-quality, reproducible research codebases with strong usability and structure
  </li>
  <li>
   Contribute to architectural decisions shaping the firm&rsquo;s ML platform and tooling ecosystem
  </li>
  <li>
   Stay close to emerging ML techniques, frameworks, and hardware developments, integrating where valuable
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You&rsquo;ll Bring&hellip;
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   3-8 years&rsquo; experience in machine learning engineering, applied ML, or similar technical roles
  </li>
  <li>
   Strong academic or practical grounding in mathematics (e.g. optimisation, linear algebra, probability)
  </li>
  <li>
   Experience building ML systems end-to-end, from experimentation through to production deployment
  </li>
  <li>
   Hands-on experience with modern ML frameworks (e.g. PyTorch, JAX, TensorFlow or similar)
  </li>
  <li>
   Proven ability to structure and maintain clean, reliable, and reproducible research code
  </li>
  <li>
   Solid software engineering fundamentals, including system design and API development
  </li>
  <li>
   Genuine interest in state-of-the-art ML research and willingness to explore new techniques
  </li>
  <li>
   Ability to critically assess modelling approaches and choose appropriate methods for different problems
  </li>
  <li>
   Strong communication skills and ability to collaborate closely with researchers and engineers
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  ...
 </p>
</div>


Machine Learning Platform Engineer (Research-Focused) | Technology-Driven Quantitative Trading Firm

JPMorganChase

<div><b>JOB DESCRIPTION</b><p><br>
Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team</p><p>
As a Software Engineer III (Machine Learning Platform Engineer) at JPMorgan Chase within the Consumer &amp; Community Banking (CCB) line of business, you serve as a seasoned member of an agile team focused on building, scaling, and maintaining robust machine learning platforms. You will design and deliver trusted, market-leading infrastructure and tools that empower data scientists and ML engineers to develop, deploy, and monitor models efficiently and securely. You are responsible for implementing critical technology solutions across multiple technical areas to support the firm&rsquo;s business objectives and drive innovation in ML platform capabilities.</p><p><b>
Job responsibilities</b></p><ul><li>
Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows.</li><li>
Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.</li><li>
Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions.</li><li>
Implement secure, high-quality production code for platform services, APIs, and automation pipelines.</li><li>
Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations.</li><li>
Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement.</li><li>
Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.</li><li>
Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.</li><li>
Contribute to the ML platform engineering community of practice and participate in events that explore new and emerging technologies.</li></ul><p><b>
Required qualifications, capabilities, and skills</b></p><ul><li>
Formal training or certification on software engineering concepts and 3+ years applied experience</li><li>
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure</li><li>
Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
</li><li>Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
</li><li>Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure</li><li>
Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring</li><li>
Experience developing APIs and platform services for ML workflows
</li><li>Solid knowledge of the software development life cycle and agile methodologies
</li><li>Ability to collaborate with cross-functional teams to deliver platform solutions aligned with business objectives
</li></ul><p><b>Preferred qualifications, capabilities, and skills</b></p><ul><li>
Familiarity with Databricks for scalable data engineering and ML platform integration</li><li>
Experience working with Snowflake for cloud-based data warehousing and analytics</li><li>
Exposure to Snorkel AI for programmatic data labeling and training data management</li><li>
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)</li><li>
Familiarity with feature stores, model registries, and ML metadata management</li><li>
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)</li><li>
Experience with RESTful APIs and microservices architectures</li></ul>
<b>ABOUT US</b><p><br>
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
</p><p></p><p>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
</p><p></p><p>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.</p><p></p><p>
Equal Opportunity Employer/Disability/Veterans</p><br>
<br>
<br>
<b>ABOUT THE TEAM</b><br>
<div>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div><div><br>
<br>
</div><div>The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.</div></div>

Software Engineer III - Machine Learning Platform

Millennium Management

<div>Data Engineer - Trading Technology Infrastructure<p></p><p>
The Trading Technology Infrastructure team at Millennium is responsible for providing shared services to internal trading systems. We are seeking a Data Engineer to join our global development team in the buildout of our strategic real-time data platform. This platform is critical for ingesting, storing, enriching, and distributing high-quality reference data from multiple sources in real time to support the development of a global order management system and other core trading services.<br>
This role has a strong focus on reference data engineering and the application of AI-driven techniques to improve data quality, automation, monitoring, and operational efficiency.<br>
<br>
<b>Key Responsibilities</b></p><ul><li><p>
Design, develop, and maintain scalable real-time and batch data pipelines for reference data ingestion, processing, and distribution.</p></li><li><p>
Build and enhance shared data services that support mastering, validation, enrichment, and delivery of critical trading reference data.</p></li><li><p>
Work closely with engineering teams and stakeholders to ensure seamless platform integration across trading systems.</p></li><li><p>
Deliver high-quality data solutions with quick turnaround times while adhering to best practices, governance standards, and production controls.</p></li><li><p>
Apply AI-enabled approaches to improve data validation, anomaly detection, metadata management, and support automation.</p></li><li><p>
Take ownership of tasks and proactively identify opportunities to improve the overall platform, development lifecycle, and infrastructure.</p></li></ul><p><b><br>
Required Skills / Experience</b></p><ul><li><p>
Trading Domain Knowledge: Strong understanding of reference data management within the trading domain, especially user, instrument, and destination master data.</p></li><li><p>
Data Engineering Experience: 7+ years of professional experience building data management, integration, or data platform solutions in production environments.</p></li><li><p>
Programming: Strong hands-on development skills in Python and/or Java.</p></li><li><p>
Database Knowledge: Proficient in database concepts across SQL and NoSQL technologies, with a focus on data integrity, scalability, and performance.</p></li><li><p>
Data Structures &amp; Algorithms: Strong understanding of data structures and algorithms relevant to distributed data processing and reference data systems.</p></li><li><p>
Communication Skills: Strong communication skills for effective interaction with team members and stakeholders across technology teams.</p></li><li><p>
Ownership Mindset: Self-starter and critical thinker who takes ownership of projects and proactively suggests infrastructure and platform improvements.</p></li><li><p>
Continuous Delivery: Experience building and supporting systems using continuous integration and continuous deployment practices.</p></li></ul><p><b><br>
Preferred Skills / Experience</b></p><ul><li><p>
Experience with real-time data platforms and event-driven architectures.</p></li><li><p>
Familiarity with AI/ML techniques for data quality monitoring, intelligent matching, anomaly detection, or workflow automation.</p></li><li><p>
Experience with PostgreSQL or other relational databases for data storage and retrieval.</p></li><li><p>
Familiarity with GraphQL for efficient data access and integration.</p></li><li><p>
Experience with AWS for cloud-based data solutions.</p></li><li><p>
Background in trading infrastructure, order management systems, or front-office data platforms.</p></li></ul><p></p><p><b>
Additional Information</b><br>
This role involves the full data lifecycle, from requirements and design through implementation, testing, and production release. The platform will support new business initiatives and help decommission legacy infrastructure. Strong collaboration skills are essential, as the role requires direct interaction with other technology teams across the Millennium organization. If you are a seasoned Data Engineer with experience in trading infrastructure, reference data, and modern AI-enabled data solutions, we encourage you to apply.</p><p></p><p>
Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. When finalizing an offer, we take into consideration an individual&rsquo;s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.</p></div>

Data Engineer - Trading Technology Infrastructure

Gambit Technologies

<div>
 <p>
  <strong>
   Senior Data Engineer | NYC Hybrid (4 Days per-week Onsite)
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  High-impact role. Real ownership. Build something that actually matters.
 </p>
 <p>
  We&rsquo;re partnering with a large, mission-driven organization tackling complex challenges across public impact initiatives. They&rsquo;re investing heavily in modernizing their data platform and are looking for a senior, hands-on engineer to lead the charge.
 </p>
 <p>
  This is not a maintenance role. You&rsquo;ll help define the future state.
 </p>
 <p>
  <br/>
 </p>
 <p>
  What You&rsquo;ll Be Doing
 </p>
 <p>
  You&rsquo;ll sit at the intersection of engineering and strategy, helping transition a legacy BI environment into a modern, cloud-native data platform.
 </p>
 <ul>
  <li>
   Design and build a cloud-based data warehouse or lakehouse from the ground up
  </li>
  <li>
   Lead the migration from an on-prem SQL Server BI stack to scalable cloud architecture
  </li>
  <li>
   Build and optimize data pipelines that actually perform at scale
  </li>
  <li>
   Own data modeling, testing, observability, and CI/CD best practices
  </li>
  <li>
   Reduce technical debt and stabilize production systems during the transition
  </li>
  <li>
   Partner directly with business stakeholders to deliver meaningful insights
  </li>
  <li>
   Help define standards and mentor others on the team
  </li>
 </ul>
 <p>
  Current Environment
 </p>
 <ul>
  <li>
   SQL Server (data warehouse)
  </li>
  <li>
   Tableau (primary BI tool)
  </li>
  <li>
   Evolving toward modern cloud data platforms
  </li>
 </ul>
 <p>
  What You Bring
 </p>
 <ul>
  <li>
   Strong hands-on Tableau experience (non-negotiable)
  </li>
  <li>
   Deep SQL skills, including large-scale query optimization
  </li>
  <li>
   Proven experience with data modeling for analytics/reporting
  </li>
  <li>
   Experience working with business stakeholders, not just hiding behind code
  </li>
  <li>
   Ability to translate messy data into clear, actionable insights
  </li>
 </ul>
 <p>
 </p>
</div>


Senior Data Engineer

NTT DATA

<b>Req ID:</b> 370261
<br><br>
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
<br><br>
We are currently seeking a AI Solutions Engineer - HYBRID to join our team in New York, New York (US-NY), United States (US).
<br><br>
Improve the end-to-end developer experience of AI development tools. Identify friction points, drive workflow improvements, and raise adoption by making AI tooling faster, clearer, and more reliable for developers in their daily work.
<br><br>
<b>Day to Day Responsibilities:</b><br>
<ul>
<li>Partner with developers across teams to identify friction points with current AI tools and workflows.</li>
<li>Design and implement UX and workflow improvements (commands, shortcuts, templates, defaults, onboarding flows).</li>
<li>Enable and improve context engineering practices for existing AI-assisted development tools in collaboration with the Context Engineering Specialist.</li>
<li>Instrument usage and feedback to quantify impact of improvements.</li>
<li>Produce guidance, examples, and enablement content to help teams adopt improved patterns.</li>
<li>Contribute to knowledge transfer and handover to steady-state teams.</li>
</ul>
<b>Minimum Skills:</b><br>
<ul>
<li>4+ years experience, including recent hands-on use of AI-assisted development tools.</li>
<li>4+ years experience shipping developer-facing improvements (internal tools, SDKs, CLIs, IDE extensions, or platform workflows).</li>
<li>4 Years of coding in Python and/or TypeScript; comfortable touching shared code and context repositories.</li>
</ul>
•
<br><br>
<b>Preferred Skills:</b><br>
<ul>
<li>Background in DevEx, platform engineering, or internal developer platforms.</li>
<li>Experience authoring or improving LLM prompts, skills, or plugins in production.</li>
<li>Familiarity with developer telemetry / observability (usage analytics, A/B testing of dev tools).</li>
<li>Financial services experience.</li>
</ul>
User-centric mindset with experience gathering developer feedback and measuring adoption.
<br><ul>
<li>Excellent written and verbal communication.</li>
<li>On-site at Alpharetta, GA or New York City, NY</li>
</ul>
Education
<br>Bachelor's degree in Computer Science, Software Engineering, or related technical field (or equivalent professional experience).
<br><br>
#LI-NorthAmerica
<br><br>
Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting pay range for this remote role is $104,904 - $218,550. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.
<br><br>
About NTT DATA
<br><br>
NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in RD.
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Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.
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NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

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