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Ai In Finance Jobs (NOW HIRING)

Finance AI Architect

Mountain View, CA · On-site

$160K - $240K/yr

Role The Finance AI Architect will bring deep financial domain expertise (investment research ... This role is central in helping customers unlock outcomes/use cases and integrate Samaya's powerful ...

Senior Manager, Finance Data Governance

San Francisco, CA · Hybrid

$128.40K - $175K/yr

In an era where AI is redefining financial velocity, data integrity is our most valuable currency. You will sit at the intersection of cutting-edge AI innovation and rigorous financial compliance ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

We support CFOs in meeting the growing demands for real-time financial decision-making by advising, implementing, and operating innovative AI solutions. Qualifications Required: * 7+ years of ...

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Ai In Finance information

See salary details

$25K

$92.6K

$135.5K

How much do ai in finance jobs pay per year?

As of May 31, 2026, the average yearly pay for ai in finance in the United States is $92,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $109,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI professional in Finance, and why are they important?

To thrive as an AI professional in Finance, you need a strong background in data science, machine learning, quantitative analysis, and finance, often supported by degrees in computer science, mathematics, or finance. Familiarity with programming languages like Python or R, experience with AI/ML frameworks (such as TensorFlow or PyTorch), and understanding of financial systems or regulatory standards are typically required. Strong analytical thinking, attention to detail, and effective communication skills set top performers apart in this field. These skills are vital for developing robust AI solutions that drive financial insights, improve decision-making, and ensure regulatory compliance.

How do professionals in AI in Finance typically collaborate with other departments within a financial institution?

Professionals working in AI in Finance often collaborate closely with teams such as risk management, compliance, and data engineering. They work together to define business requirements, ensure the quality and security of financial data, and interpret AI models’ results for practical decision-making. Effective communication is key, as AI specialists must translate complex technical findings into actionable insights for non-technical stakeholders. This collaborative environment fosters innovation and helps drive solutions that align with both regulatory standards and business goals.

What is AI in finance?

AI in finance refers to the use of artificial intelligence technologies and machine learning algorithms to automate, enhance, and optimize various financial services and processes. This includes applications such as fraud detection, algorithmic trading, credit risk assessment, customer service chatbots, and personalized financial advice. By leveraging large datasets and advanced analytics, AI can improve decision-making, reduce operational costs, and deliver more accurate and timely financial insights. Many financial institutions are increasingly adopting AI to stay competitive and comply with regulatory requirements.

What is the difference between Ai In Finance vs Data Analyst in Finance?

AspectAi In FinanceData Analyst in Finance
Required CredentialsDegree in Finance, Computer Science, or related fields; knowledge of AI and machine learningDegree in Finance, Statistics, or related fields; proficiency in data analysis tools
Work EnvironmentTech-driven finance teams, AI development labs, financial institutionsFinancial firms, banks, investment companies, data analysis departments
Employer & Industry UsageFinancial technology companies, banks integrating AI solutionsFinancial services firms analyzing market data, risk, and client information

Ai In Finance focuses on developing and implementing AI solutions within finance, requiring technical and financial expertise. Data Analysts in Finance interpret financial data to support decision-making. While both roles work with financial data, Ai In Finance emphasizes AI development, whereas Data Analysts focus on data interpretation and reporting.

More about Ai In Finance jobs
What cities are hiring for Ai In Finance jobs? Cities with the most Ai In Finance job openings:
What states have the most Ai In Finance jobs? States with the most job openings for Ai In Finance jobs include:
Infographic showing various Ai In Finance job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 15% Full Time, and 84% Part Time. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.

Finance AI Architect

Samaya AI

Mountain View, CA • On-site

$160K - $240K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 26 days ago


Job description

Role
The Finance AI Architect will bring deep financial domain expertise (investment research, asset management, trading, investment banking, risk, etc.) to advance Samaya's adoption across key institutions. This role is central in helping customers unlock outcomes/use cases and integrate Samaya's powerful AI Agents into their workflows.
Responsibilities
  • Partner with Account Executives and sales leadership to support the full sales cycle - from discovery to closing - by bringing domain expertise, technical fluency, and consultative insight
  • Engage senior stakeholders (portfolio managers, heads of research, quant leads, CIOs) in deep conversations about how Samaya can transform current workflows (e.g. due diligence, modeling, sourcing signals, thematic research, scenario analysis)
  • Lead tailored demos and workshops in financial workflows (e.g. valuation, deal modeling, stress testing, sector analysis, risk-scenario simulation), validating use cases and aligning to stakeholder pain points
  • Serve as a trusted advisor: educate customers on AI's potential (and limitations) in financial settings, and help them design adoption pathways
  • Capture feedback and act as the "Voice of the Customer," influencing product roadmap, prompt engineering strategies, domain expansions, and sales positioning
  • Collaborate with marketing and enablement to produce thought leadership, case studies, and domain-specific collateral that resonates with finance audiences
  • Stay abreast of trends in finance, fintech, AI, and the competitive landscape. Provide competitive intelligence and market insights to GTM and product teams
  • Occasionally travel (customer visits, industry events) to strengthen relationships and market presence
Experience
Required
  • 3+ years of experience in a financial expert role (e.g. investment banking, equity/credit research, asset management, trading desk, quant analytics, portfolio management)
  • Deep understanding of financial workflows: modeling, valuation, forecasting, risk management, company analysis, event-driven theme evaluation, etc
  • Proven ability to engage and influence senior decision-makers (C-suite, heads of research, CIOs), especially in finance
  • Excellent presentation and communication skills - able to translate AI capabilities into customer vernacular and deliver custom demos
  • Ability to translate ambiguous business challenges into concrete technical/AI-enabled solutions
  • A proactive, self-driven, and flexible mindset - you'll be operating in a fast-moving startup environment
  • Comfort working across teams (Product, ML, Engineering, Sales) and serving as the domain translator

Preferred
  • Advanced degree (MBA, CFA, CQF, MSc Finance, etc.)
  • Prior experience in risk, quant, or trading systems
  • B2B sales, pre-sales, or solution engineering experience in fintech or deep-tech companies
Compensation
On Target Earnings (OTE): $160,000 - $240,000 (70/30 split - base/variable). Variable compensation components will be tied to sales outcomes/success.
Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.
Equity may also be considered as part of the overall compensation package.
Benefits
Health:Access comprehensive health insurance, including medical, dental, vision, flexible spending account (FSA), and short-term disability.
Wealth: Support for your long-term financial wellbeing with a 401(k) and pre-tax benefits (e.g. commuting).
Rest: Enjoy flexibility to rest and recharge as needed, with unlimited PTO (Paid Time Off).
Flexibility:Work flexibly with a hybrid setup - typically team members spend a minimum of three days in the office per week.
Travel:Grow and connect with a travel budget that encourages conference attendance, customer visits, and team gatherings.
Equipment: Create your ideal workspace with an office Equipment allowance to set up what works best for you.
Inclusive Hiring
Interview Accommodations: We are committed to ensuring an equitable selection process for everyone and welcome applicants from varied backgrounds to enrich our team. If you require accommodations or adjustments during our recruitment process, please inform us.
Equal Opportunity Employer: We do not discriminate on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.
Visa Sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
About Samaya
Samaya builds Expert AI Agents that turn information from the global financial market into investment conviction.
The global financial market is the largest and most valuable information ecosystem in the world, connecting billions of people, influencing every type of productive human activity, and driving tens of trillions of dollars of value. At its core is investment decision-making: identifying areas of productive activity, allocating resources, carried out by millions of people across the globe.
But that process is at a breaking point. The past two decades have brought an exponential increase in market complexity: more information sources, more asset types, more disruptive themes like AI reshaping every corner of the market. For investors, this means exponentially more depth, breadth, and speed required on every decision.
The response is a forced tradeoff: zoom in on a sector or basket of companies and manage the flood, but lose sight of adjacent dynamics that move markets. Or zoom out to track broad themes, but lose the needle-in-a-haystack details that drive precise decisions. No market sector evolves in isolation, and this lack of a simultaneously zoomed-in and zoomed-out picture costs hundreds of billions in missed or suboptimal investment decisions every year.
Samaya was founded to reimagine investment decision-making across the global financial market. General-purpose AI can't reason about cause and effect across complex economic systems, embed firm-specific context, or execute reliably over long-horizon workflows. We built something different: a purpose-built AI system combining proprietary financial reasoning models, a long-horizon execution engine with persistent memory, and full auditability. Built by a team from Google DeepMind, Meta, Microsoft, and Stanford with 100+ papers and 50k+ citations, it achieves 98% accuracy on financial reasoning tasks where generic LLMs reach 53%. The result is AI that learns how each investor thinks and seamlessly takes them from information to conviction.
Our user base has scaled to 10,000+, with partnerships spanning top financial institutions worldwide, including Morgan Stanley. We're backed by $43.5M in Series A funding led by NEA, with investors including Eric Schmidt, NVIDIA, Databricks, Yann LeCun, Jeff Dean, Marty Chavez, and Mark Cuban.
Our Operating Principles
Put Users first. Our users rely on us to do their jobs. We exist because our users trust us to help them achieve their goals. In return for this trust users place in us, we keep their needs as our top priority.
Win as a collective. We are high achievers with a drive to succeed. We build strong bonds over this shared drive. We dive in to help when one of us needs it. We're kind to each other and boost each other to succeed and grow professionally and personally. We build trust with each other by making commitments and consistently delivering on them. This trust means we genuinely support each other, embracing feedback as a tool for growth and improvement. We win by operating this way, as one team.
Focus and iterate quickly. Bias for action makes us build and learn quickly. Iterating fast requires clarity on what outcomes we are targeting and why. Prioritizing the important things, taking full ownership and initiative, making fast initial progress, and rapid iterations lead to the best outcomes.
Innovate Relentlessly. We pursue novel insights, challenging the status quo and reimagining how things are done. We aren't attached to the past when improving our product and how we work in the future. We actively invest time in innovation, thinking "outside the box" to consistently raise our standards.
Prioritize Outcomes over Egos. We are committed not to a person, an idea, or an opinion but to continuously making progress to our goals. Sometimes, our goals are ambiguous; in those moments, we iterate, learn, and move on to the next inquiry. We ask the tough questions with kindness, dropping our egos in our pursuit of evidence. For our business goals, we learn from our users. For our scientific goals, our understanding is built through rigorous experimentation, research, and observation. For our personal goals, we embrace candid feedback and collaborative learning to guide our progress.