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Financial Data Engineer Remote Jobs in Oklahoma (NOW HIRING)

Systems Software Engineer

Oklahoma City, OK · On-site +1

$148K - $175K/yr

The position is remote, but the Oklahoma City (OKC) area is preferred. Responsibilities * Develop ... financial and logistical support to the federal government. We offer a comprehensive benefits ...

Software Engineer Principal

Ponca City, OK · On-site +1

$91K - $202K/yr

Strong experience with REST, SOAP, ETL processes, data movement, and system interoperability ... This position may be eligible for remote work in select geographic locations, subject to approval ...

... and financial well-being throughout your career. Lochner provides an extensive total rewards ... Flexible Work Schedules (Hybrid or Remote, when possible) * Wellness Program for Physical and ...

Software Engineer Sr

Ponca City, OK · On-site +1

$101K - $127K/yr

Financial services or regulated industry experience. _____ Soft Skills Strong communication and ... This position may be eligible for remote work in select geographic locations, subject to approval ...

... of remote monitoring, analytics, and technical support services for NOV customers. This role ... The Senior Operations Manager collaborates closely with Sales, Product Management, Engineering ...

... financial heights we aim for. This isn't just a position; it's a chance to leave your mark on an ... engineers, nurses, and lab technicians-collaborates to enhance existing IT investments and improve ...

... financial heights we aim for. This isn't just a position; it's a chance to leave your mark on an ... engineers, nurses, and lab technicians-collaborates to enhance existing IT investments and improve ...

... FTWT, Remote Areas of Interest: Business/Technical Analysis; Enterprise Data; Information ... BOK Financial Securities, Inc. and BOK Financial Private Wealth, Inc. BOKF, NA operates TransFund ...

$94K - $127K/yr

Financial Modeling & Transaction Support * Review and evaluate sources and uses, credit ... Coordinate with developers, lenders, investors, attorneys, and agencies. * Communicate complex ...

Showing results 41-60

Financial Data Engineer Remote information

What does a financial data engineer do in a remote role?

A Financial Data Engineer designs, builds, and maintains systems that process and analyze large sets of financial data. Working remotely, they collaborate with teams to develop data pipelines, integrate financial databases, and ensure the reliability of data used for financial analysis and reporting. They often use programming languages like Python or SQL, and work with big data tools to support data-driven decision-making for financial institutions or fintech companies. Their work is crucial to transforming raw financial data into actionable insights.

What are the typical challenges faced by remote financial data engineers when collaborating with cross-functional teams?

Remote Financial Data Engineers often work closely with data analysts, software developers, and business stakeholders across different time zones. One common challenge is ensuring effective communication and alignment on project requirements, especially when dealing with complex financial data pipelines and evolving business needs. Utilizing collaborative tools, maintaining clear documentation, and participating in regular virtual meetings can help bridge gaps and foster productive teamwork. Staying proactive about updates and being responsive to feedback are key to ensuring smooth collaboration in a remote environment.

What are the key skills and qualifications needed to thrive as a financial data engineer in a remote role?

To thrive as a Financial Data Engineer (Remote), you need strong programming skills (such as Python or SQL), experience with data modeling, and a background in finance or quantitative analysis, often supported by a relevant degree. Proficiency with big data platforms (like Hadoop or Spark), ETL tools, and cloud data services (such as AWS or Azure) is typically required, alongside certifications in data engineering or finance. Excellent problem-solving, communication, and time management skills help you collaborate effectively and independently in a distributed environment. These capabilities are crucial for building reliable financial data pipelines, ensuring data quality, and supporting timely, data-driven business decisions.
What are the most commonly searched types of Financial Data Engineer jobs in Oklahoma? The most popular types of Financial Data Engineer jobs in Oklahoma are:
What are popular job titles related to Financial Data Engineer Remote jobs in Oklahoma? For Financial Data Engineer Remote jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Financial Data Engineer Remote jobs in Oklahoma look for? The top searched job categories for Financial Data Engineer Remote jobs in Oklahoma are:
What cities in Oklahoma are hiring for Financial Data Engineer Remote jobs? Cities in Oklahoma with the most Financial Data Engineer Remote job openings:
Infographic showing various Financial Data Engineer Remote job openings in Oklahoma as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 10% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Oklahoma City, OK • Remote

$99K - $130K/yr

Full-time

Posted 27 days ago


Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems)

AMC Health · Remote (US) · Full-time

The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real-time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you'll work across

Real-time voice AI

  • Streaming, low-latency speech-to-speech systems built on modern LLMs
  • Telephony and real-time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency-sensitive path, where p99 matters and a stall is something a caller hears

LLM engineering

  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi-model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM-as-judge and automated agent-tests-agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure

Traditional (non-LLM) machine learning

  • End-to-end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real-world data; calibration and explainability for non-technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines

Cloud and infrastructure

  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least-privilege access, strict data-handling discipline
  • Observability and telemetry-driven debugging, tracing a production issue from a metric anomaly to root cause

Plus occasional full-stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you'll actually do

  • Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch-analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Must-haves

  • 7+ years building and operating production backend systems, with strong general-purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands-on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data

Nice-to-haves

  • Real-time media or telephony experience
  • Front-end / full-stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)

How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

Work authorization (no exceptions)

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply

Please submit both of the following:

  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.