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About This Role
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Job Summary
The Senior Staff Software Engineer – Agentic AI will design and deliver core agent capabilities, including policy execution, reasoning, orchestration, and failure‑handling. They will build production‑ready agent runtimes—state and memory systems, planners, and tool‑routing components—while ensuring safety, reliability, latency, and cost efficiency. This role will contribute to multi‑agent workflows for classification, routing, reconciliation, anomaly detection, and decisioning. The role includes implementing deterministic paths where needed, integrating graph/RAG memory, and establishing strong observability and evaluation pipelines. You will mentor engineers and help uphold high engineering standards across the team. Essential Job Functions
- Design and enhance multi‑agent frameworks and LLM‑powered autonomous systems using goal schemas, planner‑executor patterns, and well‑defined policy enforcement points. Contribute to the definition and implementation of agent state and memory architectures (short‑/long‑term, episodic, semantic) with strong PII‑minimization practices and appropriate TTL strategies. \- (20%)
- Implement and refine ReAct, CoT, and ToT reasoning loops, and help standardize their use across agent workflows. Build offline and online evaluation signals using curated golden datasets. Contribute to defining and implementing agent‑to‑agent communication protocols using frameworks like LangGraph, AutoGen, or CrewAI. \- (15%)
- Measure and improve agent decision reliability using tools such as LangSmith, Arize Phoenix, and Weights \& Biases. Design deterministic tool‑chaining patterns with appropriate fallbacks, and implement safeguards including idempotency, retries, and circuit‑breaker logic. Contribute to integrating grounding techniques to ensure accurate and reliable agent behavior. \- (15%)
- Architect and implement safety controls such as scoped tool access, allow/deny actions, validators, red‑team hooks, and human‑escalation paths. Use AgentSpec to define and apply Policy Enforcement Points (PEPs) that prevent high‑risk or irreversible agent actions. \- (15%)
- Operate and scale production agentic AI platforms on Kubernetes by defining agent‑centric SLOs, instrumenting deep telemetry (reasoning quality, hallucination rates, tool latency), and supporting on‑call through agent‑assisted triage, automated rollback/roll‑forward, and human‑gated controls. \- (15%)
- Establish enterprise safety guardrails, ethical guidelines, and compliance standards to ensure agents operate within legal, regulatory, and organizational boundaries, especially in high‑risk or financial workflows. \- (10%)
- Partner with Product to shape AI strategy and agent user experiences, and collaborate with data and backend teams to ensure agents access high‑quality, real‑time data across SQL systems, CRMs, SaaS platforms, APIs, and event streams within existing architectures. \- (5%)
- Communicate complex agentic concepts—such as CoT, RAG, and safety controls—to non‑technical stakeholders to build trust and organizational readiness. Model resilience around model failures and promote AI‑native engineering practices, including prompt design and evaluation techniques, across teams. \- (5%)
Minimum Qualifications
- Bachelor’s Degree in Computer Science or related field of study.
- 12\+ years of experience in Software Engineering including 2\+ years in AI/ML, LLMs, agent\-based systems or large\-scale distributed systems (e.g., LLM\-powered applications, LangChain, LangGraph, AutoGen) and 3\+ years of experience implementing IaC (Terraform or Ansible).
Preferred Qualifications
- Master’s Degree in Computer Science or related field of study.
- 15\+ years of experience in Software Engineering including3\+ years of experience in AI/ML, Generative AI, or agentic systems (e.g., LLM\-powered applications, LangChain, LangGraph, AutoGen), 4\+ years of experience in Fintech/payments integrations; PCI and data protection familiarity and 4\+ years of experience in implementing IaC (Terraform or Ansible).
Skills
- Agent Based Modeling
- Amazon Web Services (AWS)
- Datadog
- OpenAI
- Grafana
- Graph Databases
- Large Language Models (LLMs)
- PostgreSQL
- Prometheus (Software)
- New Relic
- Redis
- Telemetry
Reports To: Director and above
Direct Reports: 0
Work Environment
- Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if within 60 miles of a Bread Financial location. On\-call rotation to include evenings or weekends.
Physical and Mental Requirements
To perform this job successfully, an individual must be able to perform each essential job function satisfactorily and meet the physical, mental and work environment requirements. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform essential job functions, absent undue hardship.
- Communicate/Hearing
- Communicate/Talking
- Typing/Writing
Other Duties
This job description is illustrative of the types of duties typically performed by this job. It is not intended to be an exhaustive listing of each and every essential function of the job. Because job content may change from time to time, the Company reserves the right to add and/or delete essential functions from this job at any time.
Salary Range (unless otherwise noted below):
$155,600\.00 \- $333,300\.00Full Salary Range for position:
California: $178,900\.00 \- $416,600\.00
Colorado: $155,600\.00 \- $349,900\.00
New York: $171,100\.00 \- $416,600\.00
Washington: $163,300\.00 \- $383,300\.00
Maryland: $163,300\.00 \- $366,600\.00
Washington DC: $178,900\.00 \- $383,300\.00
Illinois: $155,600\.00 \- $366,600\.00
New Jersey: $178,900\.00 \- $383,300\.00
Vermont: $155,600\.00 \- $333,300\.00
Ohio: $155,600\.00 \- $333,300\.00
Maine: $155,600\.00 \- $333,300\.00
Connecticut: $171,100\.00 \- $366,600\.00
Virginia: $155,600\.00 \- $333,300\.00 *The actual base pay within this range may be dependent upon many factors, which may include, but are not limited to, work location, education, experience, and skills.*
You must be work authorized in the United States on a full time basis without the need for any sponsorship now or in the future from any employer or organization. The Company cannot offer employment to F\-1 (student) visa holders.
Bread Financial offers medical, prescription drug, dental, vision, and other voluntary benefits (including basic and optional life insurance, supplemental medical plans, and short and long\-term disability) to eligible associates (regular full\-time associates scheduled to work 30 hours per week or more) and their spouses/domestic partners, and child(ren) under the age of 26\. New associate elected coverage begins on date of hire (with the exception of disability coverage which has a 6\-month waiting period). Six weeks of 100% paid parental leave for eligible parents is available after a 180\-day waiting period. Hired associates can immediately enroll in Bread Financial’s 401(k) plan.
All associates receive 11 paid holidays. Associates have discretion in managing their time away from work through the Flexible Time Off (FTO) program and may need to notify and receive approval from their manager prior to taking the time off. Associates (except those located in Illinois) receive 80 hours of Paid Sick and Safe Time (“PSST”) upon hire and at the beginning of each subsequent calendar year. Illinois associates receive 40 hours of Illinois PSST upon hire and at the beginning of each subsequent calendar year and 40 hours of Illinois Paid Leave upon hire and at the beginning of each subsequent calendar year. Illinois Paid Leave must be used before associates in Illinois will be approved to take FTO.
Hired associates will be able to elect the purchase company stock during offering periods in June and December. You will be eligible for an annual incentive bonus based on individual and company performance.
Click here for more Benefits information.
About Bread Financial®
At Bread Financial, you’ll have the opportunity to grow your career, give back to your community, and be part of our award\-winning culture. We’ve been consistently recognized as a best place to work nationally and in many markets and we’re proud to promote an environment where you feel appreciated, accepted, valued, and fulfilled—both personally and professionally. Bread Financial supports the overall wellness of our associates with a diverse suite of benefits and offers boundless opportunities for career development and non\-traditional career progression.
Bread Financial® (NYSE: BFH) is a tech\-forward financial services company that provides simple, personalized payment, lending and saving solutions to millions of U.S. consumers. Our payment solutions deliver growth for some of the most recognized brands in travel \& entertainment, health \& beauty, technology, electronics, jewelry, home and specialty apparel through our co\-brand and private label credit cards and pay\-over\-time products providing choice and value to our shared customers. Additionally, we offer Bread Financial general purpose credit cards and saving products that empower our customers and their passions for a better life.
Bread Financial proudly marks 30 years of success in 2026\. To learn more about our global associates, our performance and our sustainability progress, visit breadfinancial.com or follow us on Instagram and LinkedIn.
- Bread Financial offers competitive pay, a comprehensive selection of benefit options including 401(k).
- The Company is an Equal Opportunity Employer.
- Any applicant offered employment will be required to establish that they are legally authorized to work in the United States for the Company.
- The Company participates in E\-Verify.
- The Company will consider for employment all qualified applicants, including those with a criminal history, in a manner consistent with the requirements of all applicable federal, state, and local laws, including the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act. Applicants with criminal histories are encouraged to apply.
- The Company complies with the Americans with Disabilities Act (ADA), as amended, and all applicable state/local laws. The Company will provide accommodations to applicants needing accommodations to complete the application process. Applicants with disabilities may contact the Company to request and arrange for accommodations. If you need assistance to accommodate a disability, you may request an accommodation at any time. Please contact the Recruiting Team at [email protected].
Job Family:
Information TechnologyJob Type:
Regular
Salary Context
This $155K-$383K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Bread Financial, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($269K) sits 23% above the category median. Disclosed range: $155K to $383K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Bread Financial AI Hiring
Bread Financial has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Based in Columbus, OH, US. Compensation range: $278K - $383K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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