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Senior Vice President, Infrastructure Engineering (Mainframe Communications Systems Software Engineer
ewminds consulting Services
Jersey City, NJ
(SVP) Senior Vice President, Infrastructure Engineering (Mainframe Communications Systems Software Engineer)
Added just now
Senior Forward Deployed Engineer (FDE Lead
ewminds consulting Services
East Pittsburgh, PA
Hands-on experience building backend services, APIs, and scalable production systems.
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Vice President – Full Java Stack Engineer
ewminds consulting Services
Pittsburgh, PA
We are seeking a Vice President – Full Stack Engineer to join a mission-critical engineering team supporting a high-performance, regulated enterprise platform. This is a hands-on…
Added 1 min ago
CO
Chief of Traffic Engineering
City of Jacksonville
Jacksonville, FL
- $67.31 to $79.59 USD / hour
Shall be registered as a Professional Engineer.
Added 1 min ago
OA
Senior Infrastructure Software Engineer
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Seattle, WA
- $200,000 to $240,000 USD / year
Overland AI is building off-road autonomy, and our software infrastructure is the backbone that enables our teams to move fast, experiment safely, and ship mission-critical systems. As an…
Added 2 mins ago
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Controls and Automation Engineer
Phoenix Tailings
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- $80,000 to $150,000 USD / year
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Added 3 mins ago
Hotel Engineer | Hotel Indigo Austin | Holiday Inn Express Downton Austin
Crescent Hotels & Resorts
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We are seeking a skilled and hands-on Preventative Maintenance Engineer to join our team. This role is responsible for maintaining the overall upkeep, safety, and appearance of the hotel by…
Added 3 mins ago
Software Development Engineer II, Client Engineering
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Process Design Engineer, Quick Commerce Design Engineering
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Quick Commerce Process Design is looking for an innovative, solutions-oriented Process Design Engineer to help build the operational processes and standards behind Amazon's next-generation,…
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Sr. System Development Engineer, Amazon Leo
Amazon Kuiper Manufacturing Enterprises LLC
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The role: In this role, you will be a key member of the team building and operating AWS infrastructure that supports the organization’s business services. You will provide infrastructure…
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Automation Engineer
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As an Automation Engineer, you will play a crucial role in maximizing equipment reliability and operational performance in our fulfillment centers by providing proactive controls automation…
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Data Engineer, SPTC
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Data Engineer, Selling Partner Trust
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Austin, TX · Seattle, WA · Irving, TX
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Software Development Engineer, iOS
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Director of Engineering | Thompson Austin/tommie Austin
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Lead Principal Application Software Engineer
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- $104,600 to $264,100 USD / year
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Adopt positive attitude of accountability by providing reliable, constructible, affordable, and timely solutions (RCAT) resulting in Providence being the Engineer of Choice.
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Designer, Structural
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York, PA
Adopts positive attitude of accountability by providing reliable, constructible, affordable, and timely solutions (RCAT) resulting in Providence being the Engineer of Choice.
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…expand, we are seeking a motivated and driven Quality Assurance Engineer to join our…
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Civil Engineer I - Foundations, Structural Analysis & FBD | $45.43/hr
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- $45.43 USD / hour
Our client, a global leader in energy infrastructure and advanced industrial engineering, is seeking a Civil Engineer I - Structural Analysis & Foundations Engineer to join their team. As a…
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Operating Engineer - HVAC Engineer
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Our client, a leading commercial real estate and facilities management organization, is seeking an Operating Engineer to join their team. As an Operating Engineer, you will be part of the…
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Product Engineer
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- $120,000 to $200,000 USD / year
Join a consumer fintech product and engineering team building tools that help people manage cash flow and build credit. You will own backend features from design through production,…
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Founding Engineer
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Join the founding engineering team at an early-stage B2B SaaS company building AI tools for industrial ingredient manufacturers. This hands-on role spans product engineering, backend…

Senior AI Software Developer & Engineer (US Citizen)

Remote, United States

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Job details

Experience: 8+ years of applied AI/ML experience, including building and deploying production systems (LLMs, generative AI, and large-scale or distributed model systems).
Posting language: English
Posted: Nov 6, 2026

Original job description

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Job Type

Full-time

Description

NOTE: This is a full-time employment opportunity and open to W2, 1099, or C2C (no third parties or staffing agencies, please). The candidate MUST be a U.S. Citizen (preferred) or U.S, Permanent Resident (GC). This is a remote opportunity; candidate must be based in the U.S.; preference given to candidates in the Washington DC, Maryland, Virginia (DMV) area; ET zone work schedule.

Daily Responsibilities

Serve as a senior, hands-on full-stack AI engineer and technical authority, leading the technical strategy, design, and delivery of large-scale mission-critical AI systems supporting federal programs.
Serve as the primary technical authority, defining AI and application architecture across multiple programs.
Lead architecture for distributed, cloud-native, and hybrid AI systems.
Define and enforce reference architectures, standards, and reusable frameworks.
Establish enterprise modernization roadmaps aligned to mission outcomes, compliance, and scalability.
Drive cross-program technical decision-making to ensure interoperability, security, and long-term sustainability.
Advise senior federal stakeholders (SES-level and above) on AI adoption, modernization, and risk management.
Build full-stack AI applications end to end, from user-facing interfaces to back-end services, APIs, and data layers.
Lead design, development, and deployment of advanced AI solutions using Python as the primary development language, including large language models (LLMs) and foundation models, Retrieval-Augmented Generation (RAG) systems, agentic workflows, and orchestration frameworks.
Architect and implement scalable ML systems and services built on Python-based frameworks and APIs.
Integrate AI and LLM capabilities into existing enterprise applications and legacy platforms (e.g., content management, case management, and records systems) via APIs, middleware, and event-driven patterns.
Define and implement distributed training strategies (GPU/TPU clusters, parallelization, optimization).
Oversee full ML lifecycle in partnership with the senior data scientist: data pipelines, feature engineering, training, evaluation, deployment, and monitoring.
Drive model optimization techniques (quantization, distillation, caching) to improve performance and cost.
Establish robust MLOps practices leveraging Python-driven automation, pipelines, and tooling.
Stand up the enterprise CI/CD-to-AI/MLOps pipeline, beginning with time-boxed proofs of concept and MVP implementations that mature into production systems.
Serve as SME in federal AI policy (e.g., NIST AI RMF, OMB M-25-21 and M-25-22, Executive Order 14179).
Define and operationalize Responsible AI frameworks, including model validation and evaluation, bias mitigation and fairness, and explainability, auditability, and safety.
Ensure compliance with FISMA, FedRAMP, NIST 800-53, privacy, and Section 508 requirements.
Lead large-scale modernization initiatives (e.g., legacy-to-cloud, microservices transformation, including Python-based refactoring and re-platforming efforts).
Define repeatable modernization frameworks and accelerators.
Oversee DevSecOps pipelines, CI/CD automation, zero-trust architectures, and secure software supply chain practices.
Ensure delivery of resilient, high-availability systems in regulated federal environments.
Lead multiple concurrent engineering efforts across integrated teams.
Provide technical leadership to architects, engineers, and DevSecOps specialists, including establishing Python coding standards and engineering best practices.
Mentor senior engineers and technical leaders; elevate engineering excellence and code quality.
Support technical strategy in proposals, captures, and client engagements.
Contribute to thought leadership (whitepapers, architecture patterns, platform strategy).
Executive communication skills with experience influencing senior leaders.

Requirements

Must of a U.S. Citizen (preferred) or U.S. Permanent Resident (GC), as mandated by our government client.
Must be able to complete/pass/hold at a minimum a Public Trust Investigation / background check. An active clearance (e.g. Public Trust, Secret, or higher) is preferred.
Must be based / reside in the U.S, preference given to candidates in the DMV area.
12+ years of software engineering experience combining senior technical leadership, hands-on expertise in Python-based AI/ML systems (including large language models), and ownership of enterprise architecture, governance, and innovation.
8+ years of applied AI/ML experience, including building and deploying production systems (LLMs, generative AI, and large-scale or distributed model systems).
Expert-level Python development experience, including designing production-grade ML systems, data pipelines, and microservices-based architectures.
Hands-on experience with ML frameworks (PyTorch, TensorFlow, JAX) and distributed training (DeepSpeed, FSDP, Horovod).
Full-stack engineering skills, including front-end frameworks, back-end services, RESTful APIs, microservices, and cloud-native deployment (e.g., containers, Kubernetes).
Deep experience with cloud platforms (Azure, AWS, GCP), including FedRAMP environments and designing AI systems in cloud-native, distributed environments.
Deep expertise in machine learning and deep learning, particularly transformer-based models and LLMs.
Hands-on experience with LLM application stacks, including orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel), embeddings, vector databases, and prompt engineering.
Experience with AI platforms and architectures (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI, RAG, agents).
Proven success delivering enterprise-scale systems and modernization programs.
Strong background in microservices, APIs, distributed systems, and DevSecOps practices.
Experience managing GPU-based infrastructure or high-performance ML environments.
Demonstrated ability to translate AI research into production system.
Proven ability to integrate AI capabilities into existing and legacy enterprise systems (e.g., legacy CMS or COTS platforms) using APIs, middleware, connectors, and event-driven architectures.
Strong understanding of large-scale data systems and ML evaluation methodologies.
Experience working with sensitive data, including PII safeguards such as anonymization, masking, and data loss prevention.
Experience with enterprise integration technologies, including REST/SOAP services, message queues, ETL pipelines, and SQL/NoSQL databases.
Proficiency with managed generative AI services (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI) and integrating frontier models such as GPT, Claude, and Gemini.
Demonstrated ability to own solutions end to end - from discovery and prototyping through production deployment, integration, and ongoing support.
Ability to balance strategic vision with deep hands-on technical execution.
Excellent analytical skills, attention to detail, and strong problem-solving abilities.
Excellent communication and collaboration skills to communicate complex analytical insights to executive and non-technical stakeholders. Ability to translate ambiguous business questions into analytical solutions.
Experience with federal civilian agencies preferred.
BS or MS degree (preferred) in engineering, data science, computer science, statistics or related field.

This role is open to W2 or 1099/C2C engagements. Compensation/rate decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. $155k -$175k.

Salary Description

$155k - $175k

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More about this job

Skills

Regulatory compliance
Decision making
Risk management
Python
ML
CI/CD
Microservices
Supply chain management
Leadership
Communication skills
PyTorch
TensorFlow
API development
Kubernetes
Microsoft Azure
AWS
Google Cloud
Machine learning
Deep learning
LangChain
Research
CMS
Loss prevention
Data engineering
SQL
NoSQL
Analytical skills
Attention to detail
Problem solving
Collaboration
Computer science
Statistics

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