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State Street

AI Enablement/Orchestration Engineer - Senior Associate

State Street is hiring an AI Enablement/Orchestration Engineer - Senior Associate in Bengaluru, India. Level rates it ; you can apply on Level.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • Tools and skills the posting cites include OpenAI, Python and Generative AI.
  • Level files it as a senior role.
  • Level lists 1,200+ other open roles at State Street.
  • The role was posted in the last few days.

AI in this role

Build and operationalize generative AI systems, RAG architectures, and multi-agent workflows for financial services.

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Job Description:  AI Enablement/Orchestration Engineer

Role Summary & Role Description

Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data and insights to our clients. We’re driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation.

We offer a collaborative environment where technology skills and innovation are valued in a global organization. We’re looking for top technical talent to join our team and deliver creative technology solutions that help us become an end-to-end, next-generation financial services company.

Join us if you want to grow your technical skills, solve real problems and make your mark on our industry.

We are seeking a motivated and enthusiastic AI Enablement Engineer to join our team and contribute to the development and integration of cutting-edge AI solutions into our business processes. This is a highly technical and hands-on role where you will work closely with senior team members to build AI systems leveraging technologies such as Generative AI (Gen AI), Retrieval-Augmented Generation (RAG), Agentic AI frameworks. You will collaborate closely with software engineers and investment servicing business teams to solve complex business challenges in the payments domain.

This role requires strong capabilities in both AI Engineering and Data Engineering. You will design data products, orchestrate multi-agent workflows, develop Retrieval-Augmented Generation (RAG) systems, integrate enterprise knowledge sources, and establish the governance and observability capabilities required to operate AI safely within a highly regulated financial services environment.

State Street is accelerating the adoption of AI-enabled capabilities to improve operational efficiency, enhance cybersecurity resilience, strengthen risk management, and deliver intelligent experiences across the enterprise.

As an AI Orchestration Engineer, you will help establish the AI execution layer that enables secure collaboration between enterprise data platforms, large language models, internal knowledge repositories, agentic workflows, governance controls, and human decision makers.

What You Will Be Responsible For

  • Design, build, and operationalize AI/ML solutions to detect anomalies, exceptions, fraud indicators, operational risk signals, and process deviations across high-volume payment flows.
  • Develop anomaly detection models using supervised, unsupervised, semi-supervised, time-series, graph-based, statistical, and hybrid machine learning approaches.
  • Engineer features from payment transactions, exception events, operational logs, historical patterns, and reference data to identify unusual value, volume, velocity, counterparty, timing, currency, geography, and repair/reject behaviors.
  • Build scalable batch, streaming, and near-real-time data pipelines to support payment monitoring, detection, scoring, alert generation, and downstream investigation workflows.
  • Tune detection thresholds, scoring logic, and model sensitivity to balance early detection, precision, recall, false positive reduction, and operational usability.
  • Develop explainability capabilities, reason codes, model diagnostics, and investigation summaries to help payment operations, risk, and technology teams understand why anomalies are flagged.
  • Integrate anomaly detection services with payment applications, case management tools, workflow platforms, APIs, data stores, and human-in-the-loop review processes.
  • Use GenAI, RAG, and agentic AI capabilities selectively to support alert summarization, root-cause analysis, knowledge retrieval, operational playbooks, and assisted triage.
  • Implement MLOps practices for experiment tracking, model versioning, deployment automation, reproducibility, monitoring, rollback, and production support.
  • Monitor model performance, alert quality, drift, data quality, investigation outcomes, SLA adherence, and production reliability across anomaly detection use cases.
  • Partner with payments operations, product, risk, compliance, architecture, cybersecurity, and engineering teams to translate business scenarios into detection patterns and AI-enabled controls.
  • Apply Responsible AI, model risk management, auditability, data governance, security, and regulatory control requirements for AI solutions in a financial services environment.
  • Collaborate with cross-functional teams to identify AI use cases and translate business requirements into agent-based solutions.

Education & Qualifications

Skills Required

  • Hands-on experience building anomaly detection, fraud detection, transaction monitoring, risk scoring, or payment intelligence models using supervised, unsupervised, semi-supervised, and hybrid approaches.
  • Strong understanding of anomaly detection techniques such as clustering, isolation forests, one-class SVM, autoencoders, gradient boosting, time-series anomaly detection, graph-based detection, and statistical outlier methods.
  • Ability to engineer features from high-volume payment data, including amount, currency, value date, settlement date, counterparty, account, geography, payment type, frequency, velocity, historical behavior, exception codes, and repair/reject patterns.
  • Experience tuning detection thresholds and model sensitivity to optimize precision, recall, F1 score, alert quality, false positive reduction, and operational triage effectiveness.
  • Knowledge of payment flows, payment exceptions, duplicate payments, unusual value or volume patterns, payment repairs, rejects, sanctions referrals, cut-off breaches, and operational risk indicators.
  • Experience deploying batch, streaming, or near-real-time inference pipelines using technologies such as Kafka, Spark, Airflow, cloud data platforms, APIs, and MLOps tooling.
  • Ability to implement explainability and investigation support using SHAP, LIME, reason codes, model diagnostics, rule-model hybrids, and GenAI-assisted alert summarization.
  • Experience monitoring model drift, data quality, alert trends, investigation outcomes, SLA performance, and production reliability for anomaly detection systems.

Minimum Qualifications

  • 6+ years of professional experience; Bachelor's or Master's in Computer Science, AI/ML or related field.
  • 3–5 years of experience in Data Engineering, AI Engineering, Machine Learning Engineering, Software Engineering, or related disciplines.
  • Strong experience developing large-scale data pipelines and distributed data-processing solutions.
  • Proficiency in Python with solid software engineering fundamentals
  • Experience with SQL, APIs, workflow automation, and cloud-native architectures.
  • Solid understanding of RAG, experience with OpenAI Service and prompt engineering techniques. Knowledge of vector databases.
  • Experience integrating LLMs with external databases, APIs and storage systems
  • Experience in CI/CD-based projects. Knowledge of Docker and Kubernetes for deploying AI services
  • Strong communication and stakeholder collaboration skills.
  • Experience using Jira as an agile management tool.

Preferred Qualifications

  • Experience in Payments domain. Familiarity with payment standards and rails such as SWIFT, ISO 20022, wires, ACH, SEPA, real-time payments, and cross-border payment processing is preferred.
  • Experience in IBM MQ,  Kafka, MFT.
  • Knowledge of Responsible AI, data governance, and model risk management.

Work Schedule

Hybrid

Keywords (If any)

Why this role is important to us

Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data and insights to our clients. We’re driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation.

We offer a collaborative environment where technology skills and innovation are valued in a global organization. We’re looking for top technical talent to join our team and deliver creative technology solutions that help us become an end-to-end, next-generation financial services company.

Join us if you want to grow your technical skills, solve real problems and make your mark on our industry.

About State Street

What we do. State Street is one of the largest custodian banks, asset managers and asset intelligence companies in the world. From technology to product innovation, we’re making our mark on the financial services industry. For more than two centuries, we’ve been helping our clients safeguard and steward the investments of millions of people. We provide investment servicing, data & analytics, investment research & trading and investment management to institutional clients.

Work, Live and Grow. We make all efforts to create a great work environment. Our benefits packages are competitive and comprehensive. Details vary by location, but you may expect generous medical care, insurance and savings plans, among other perks. You’ll have access to flexible Work Programs to help you match your needs. And our wealth of development programs and educational support will help you reach your full potential.

Inclusion, Diversity and Social Responsibility. We truly believe our employees’ diverse backgrounds, experiences and perspectives are a powerful contributor to creating an inclusive environment where everyone can thrive and reach their maximum potential while adding value to both our organization and our clients. We warmly welcome candidates of diverse origin, background, ability, age, sexual orientation, gender identity and personality. Another fundamental value at State Street is active engagement with our communities around the world, both as a partner and a leader. You will have tools to help balance your professional and personal life, paid volunteer days, matching gift programs and access to employee networks that help you stay connected to what matters to you.

State Street is an equal opportunity and affirmative action employer.

Discover more at StateStreet.com/careers


About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.


We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.


As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.


Discover more information on jobs at StateStreet.com/careers


Read our CEO Statement

How we rate this

AI Enablement/Orchestration Engineer - Senior Associate at State Street rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGLLM IntegrationAI agentsML OpsAI SafetyAI EngineeringData Engineering

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How have you integrated a large language model into a production application?
  4. How do you decide when an AI agent can act on its own versus asking for approval first?
  5. How do you monitor a model once it's live, and how do you know it needs retraining?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and ML Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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