LLM Jobs in Tampa.
All active LLM roles based in Tampa.
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Strategic Account Executive - Miami/Tampa (Remote)
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Strategic Account Executive at Unframe
Location: Miami or Tampa, FL (Remote)
About Unframe
Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.
Backed by Bessemer, Craft, and TLV Partners with $50M in Series A funding, we’re building a fast-growing, revenue-generating company working with Fortune 500 customers globally
About the role:
We’re looking for Strategic AEs to join our team and help drive our go-to-market motion. You’ll play a pivotal role in landing our first major customers, shaping our sales playbook, and partnering directly with the VP of Sales and founder to build a high-performance revenue engine.
What you’ll do:
- Lead complex, multi-stakeholder sales cycles into highly regulated industries (FinServ, Healthcare, Manufacturing, Retail) where our on-premises capabilities provide a competitive advantage.
- Build pipeline from zero in an early-stage environment—identify and win strategic enterprise accounts with no hand-raisers or established playbook.
- Translate complex AI/ML capabilities into compelling business outcomes for C-suite stakeholders, positioning Unframe for companies seeking to “buy vs. build” AI capabilities.
- Architect multi-year expansion strategies and build deep relationships across IT, product, and innovation teams.
- Collaborate directly with the VP of Sales and founders to refine the enterprise strategy and influence the product roadmap
What we are looking for:
- 8+ years enterprise software sales with consistent quota over-achievement at Fortune 500 companies
- Proven track record closing $1M+ ACV deals in early-stage environments
- Experience selling complex technical solutions to CIO organizations
- Background in AI/ML platforms, digital transformation, enterprise data platforms, or management consulting
- Entrepreneurial mindset, you thrive in ambiguity, own outcomes, and build from scratch
- Success in highly regulated industries with complex compliance requirements
Nice to have:
- Regulated industry experience, early-stage success
Why join us?
- Compensation is uncapped with aggressive accelerators. At $1M+ ACV deal sizes, this structure rewards over-performance on meaningful deals.
- Our VP of Sales joined Unframe for three reasons: a founder with a proven exit, tier-one investors, and a product that's genuinely different and defensible. The GTM approach backs that up. Buyers get a free POC, tailored to their actual use case, delivered in days. No data sharing, no upfront cost, no six-month consulting engagement before anyone sees value.
- You'll work directly with the VP of Sales and founders, shape GTM strategy, close the deals that define our market position, and hold equity in a company with real institutional backing and momentum.
- We hire with intention. If you thrive in a performance culture with real backing behind you, you will win here.
Ready to Build the Future?
If this opportunity excites you, apply now!
Ready to apply?
Apply to Unframe
Principal MLOps Engineer
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This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
Who we are:
Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.
We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.
About the role:
Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.
Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.
In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.
What you’ll do:
- Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
- Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
- Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
- Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
- Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
- Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
- Improve observability, reliability, security, and maintainability across ML infrastructure and services
- Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
- Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
- Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
- Get hands-on with customers at the most forward-leaning places in the Department of War
What we are looking for:
- 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
- 5+ years of experience with Docker and Kubernetes in production environments
- 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
- Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
- Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
- Practical experience deploying machine learning workloads on Kubernetes
- Experience managing clusters or workloads that use GPUs
- Strong understanding of Helm and Kubernetes deployment patterns
- Strong scripting or programming skills, preferably in Python
- Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
- Strong troubleshooting, systems thinking, and communication skills
- Ability to work independently and collaboratively in a fast-moving environment
- Ability to obtain and maintain a Top Secret clearance
- Ability to obtain Security+ certification within the first 90 days of employment
Highly preferred:
- Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
- Experience with secure and compliant deployment practices in regulated or government environments
- Experience with Kubernetes-based ML platforms such as Kubeflow
- Familiarity with service mesh technologies such as Istio
- Experience provisioning and debugging complex CI/CD systems
- Experience with infrastructure as code tools such as Terraform
- Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
- Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
- Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
- Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What success looks like:
- You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
- ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
- Model deployments become more secure, observable, and supportable across real-world mission environments
- The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Clearance Requirements:
- Ability to obtain and maintain a Top Secret clearance
Work Type:
- Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
- May require up to 40% travel
Salary Range: $150,000.00 - $200,000.00
What we will offer you:
- Highly competitive salary
- Fully covered healthcare, dental, and vision coverage
- 401(k) and company match
- Take as you need PTO + 11 paid holidays
- Education & training benefits
- Annual budget for your tech/gadgets needs
- Monthly box of yummy snacks to eat while doing meaningful work
- Remote, hybrid, and flexible work options
- Team off-site in fun places!
- Generous Referral Bonuses
- And More!
Our Vision Statement:
We bridge the gap between humans and data through radical transparency and our obsession with the mission.
Our Customer Obsession:
We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.
How do we get there?
Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm.
Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Ready to apply?
Apply to Raft Company Website
Director, Sales East (Remote)
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Director Sales, East at Unframe
Location: East Coast, USA
About Unframe:
Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.
Backed by Bessemer, Craft, and TLV Partners with $50M in Series A funding, we’re building a fast-growing, revenue-generating company working with Fortune 500 customers globally
About the role:
We’re looking for a Director of Enterprise Sales to drive go-to-market execution within their assigned region, leading a team of Strategic Account Executives focused on new enterprise acquisition and account expansion.
You’ll partner closely with the Regional Vice President and executive leadership to drive quota attainment, improve deal execution, and scale a high-performance sales culture.
What you’ll do:
- Lead and Develop a High-Performing Team
- Manage and coach Strategic AEs, reinforcing excellence in discovery, multi-threaded engagement, forecasting discipline, and enterprise deal strategy.
- Drive Regional Pipeline and Revenue Execution
- Support team pipeline generation, deal progression, and accurate forecasting across complex, multi-stakeholder enterprise sales cycles.
- Elevate Deal Strategy
- Act as a player-coach in key opportunities, helping AEs navigate C-suite conversations, technical validation, procurement, and compliance stakeholders.
- Ensure strong CRM hygiene, forecast accuracy, pipeline inspection, and adherence to defined sales processes.
- Collaborate with Product Solutions, Partnerships, Marketing, and Customer Success to ensure seamless execution from first meeting through expansion.
- Identify regional market opportunities and provide feedback loops to influence GTM strategy and enablement programs.
What we are looking for:
- 5+ years in enterprise sales leadership or team lead roles.
- 8+ years in enterprise software sales (AI/ML, data infrastructure, digital transformation preferred).
- Experience closing and coaching $1M+ ACV enterprise deals.
- Strong forecasting discipline and pipeline management expertise.
- Deep understanding of consultative, solution-based selling.
- Entrepreneurial mindset, comfortable operating in high-growth, fast-paced environments
Nice to have:
- Experience selling into regulated industries.
- Experience building teams in early-stage or scaling SaaS environments.
- Experience operating within a multi-region enterprise GTM structure.
Why Join us?:
- Compensation is uncapped with aggressive accelerators. At $1M+ ACV deal sizes, this structure rewards over-performance on meaningful deals.
- Our VP of Sales joined Unframe for three reasons: a founder with a proven exit, tier-one investors, and a product that's genuinely different and defensible. The GTM approach backs that up. Buyers get a free POC, tailored to their actual use case, delivered in days. No data sharing, no upfront cost, no six-month consulting engagement before anyone sees value.
- You'll work directly with the VP of Sales and founders, shape GTM strategy, close the deals that define our market position, and hold equity in a company with real institutional backing and momentum.
- We hire with intention. If you thrive in a performance culture with real backing behind you, you will win here.
Ready to Build the Future?
If this opportunity excites you, apply now!
Ready to apply?
Apply to Unframe
Principal MLOps Engineer
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This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
Who we are:
Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.
We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.
About the role:
Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.
Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.
In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.
What you’ll do:
- Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
- Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
- Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
- Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
- Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
- Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
- Improve observability, reliability, security, and maintainability across ML infrastructure and services
- Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
- Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
- Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
- Get hands-on with customers at the most forward-leaning places in the Department of War
What we are looking for:
- 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
- 5+ years of experience with Docker and Kubernetes in production environments
- 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
- Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
- Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
- Practical experience deploying machine learning workloads on Kubernetes
- Experience managing clusters or workloads that use GPUs
- Strong understanding of Helm and Kubernetes deployment patterns
- Strong scripting or programming skills, preferably in Python
- Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
- Strong troubleshooting, systems thinking, and communication skills
- Ability to work independently and collaboratively in a fast-moving environment
- Ability to obtain and maintain a Top Secret clearance
- Ability to obtain Security+ certification within the first 90 days of employment
Highly preferred:
- Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
- Experience with secure and compliant deployment practices in regulated or government environments
- Experience with Kubernetes-based ML platforms such as Kubeflow
- Familiarity with service mesh technologies such as Istio
- Experience provisioning and debugging complex CI/CD systems
- Experience with infrastructure as code tools such as Terraform
- Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
- Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
- Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
- Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What success looks like:
- You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
- ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
- Model deployments become more secure, observable, and supportable across real-world mission environments
- The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Clearance Requirements:
- Ability to obtain and maintain a Top Secret clearance
Work Type:
- Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
- May require up to 40% travel
Salary Range: $150,000.00 - $200,000.00
What we will offer you:
- Highly competitive salary
- Fully covered healthcare, dental, and vision coverage
- 401(k) and company match
- Take as you need PTO + 11 paid holidays
- Education & training benefits
- Annual budget for your tech/gadgets needs
- Monthly box of yummy snacks to eat while doing meaningful work
- Remote, hybrid, and flexible work options
- Team off-site in fun places!
- Generous Referral Bonuses
- And More!
Our Vision Statement:
We bridge the gap between humans and data through radical transparency and our obsession with the mission.
Our Customer Obsession:
We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.
How do we get there?
Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm.
Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Ready to apply?
Apply to Raft Company WebsitePrincipal MLOps Engineer
Share this job
This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
Who we are:
Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.
We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.
About the role:
Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.
Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.
In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.
What you’ll do:
- Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
- Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
- Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
- Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
- Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
- Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
- Improve observability, reliability, security, and maintainability across ML infrastructure and services
- Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
- Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
- Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
- Get hands-on with customers at the most forward-leaning places in the Department of War
What we are looking for:
- 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
- 5+ years of experience with Docker and Kubernetes in production environments
- 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
- Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
- Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
- Practical experience deploying machine learning workloads on Kubernetes
- Experience managing clusters or workloads that use GPUs
- Strong understanding of Helm and Kubernetes deployment patterns
- Strong scripting or programming skills, preferably in Python
- Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
- Strong troubleshooting, systems thinking, and communication skills
- Ability to work independently and collaboratively in a fast-moving environment
- Ability to obtain and maintain a Top Secret clearance
- Ability to obtain Security+ certification within the first 90 days of employment
Highly preferred:
- Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
- Experience with secure and compliant deployment practices in regulated or government environments
- Experience with Kubernetes-based ML platforms such as Kubeflow
- Familiarity with service mesh technologies such as Istio
- Experience provisioning and debugging complex CI/CD systems
- Experience with infrastructure as code tools such as Terraform
- Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
- Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
- Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
- Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What success looks like:
- You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
- ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
- Model deployments become more secure, observable, and supportable across real-world mission environments
- The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Clearance Requirements:
- Ability to obtain and maintain a Top Secret clearance
Work Type:
- Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
- May require up to 40% travel
Salary Range: $150,000.00 - $200,000.00
What we will offer you:
- Highly competitive salary
- Fully covered healthcare, dental, and vision coverage
- 401(k) and company match
- Take as you need PTO + 11 paid holidays
- Education & training benefits
- Annual budget for your tech/gadgets needs
- Monthly box of yummy snacks to eat while doing meaningful work
- Remote, hybrid, and flexible work options
- Team off-site in fun places!
- Generous Referral Bonuses
- And More!
Our Vision Statement:
We bridge the gap between humans and data through radical transparency and our obsession with the mission.
Our Customer Obsession:
We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.
How do we get there?
Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm.
Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Ready to apply?
Apply to Raft Company Website
Senior MuleSoft Engineer
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At Green Irony, we exist to turn AI into Actual Intelligence—accelerating outcomes and proving that complexity is optional. We hire people who automate first, ask permission never, and treat ownership as a default setting. If you’d rather govern yourself than be governed by layers of project managers, welcome home.
As a Senior MuleSoft Engineer, you will design and deliver API-led integration solutions on Anypoint Platform — directly with clients, from discovery through go-live. You'll drive architecture decisions, protect margin through scope discipline, and build the kind of trusted client relationships that turn one engagement into many.
What You'll Own
You will be the technical owner of your client engagements — not a resource assigned to a ticket queue. That means:
- Client Delivery Ownership: Lead integration programs end-to-end for external clients — from discovery and estimation through SOW shaping, stakeholder alignment, and delivery KPIs (on-time, on-budget, CSAT).
- Stakeholder Management (exec → dev): Navigate the full relationship stack. Translate architecture trade-offs to executives, earn trust with engineering teams, and keep both sides aligned throughout delivery.
- Scope Discipline: Anticipate risk early, communicate trade-offs clearly, and protect margin through change-order discipline — without damaging the relationship.
- Autonomous Execution: Own your calendar, your estimates, and your commitments. No one will chase you for updates. You surface risks before they surface you.
Key Responsibilities
Technical Delivery
- Lead technical design, implementation, and deployment of large-scale MuleSoft integration and API solutions (CloudHub 2.0, Runtime Fabric, Anypoint MQ, Flex Gateway, or on-prem).
- Develop and maintain DataWeave scripts, Mule flows, and CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins).
- Enforce architectural and security standards (RAML/OAS, OAuth2, JWT, TLS, encryption).
- Monitor and optimize integrations for performance, scalability, and maintainability.
Client-Facing Services Delivery
- Lead discovery sessions, shape estimates, and contribute to SOW development — you are the technical voice in the room with the client.
- Own delivery KPIs: on-time rate ≥90%, estimate variance ≤±15%, client satisfaction scores that earn repeat business.
- Proactively communicate status, risks, and decisions — updates go out without being asked.
- Build trusted relationships that make scope conversations easier, not harder.
- When scope creeps (and it will), you call it — with a path forward, not just a flag.
Leadership & Collaboration
- Provide coaching and technical guidance to engineers; lead code reviews and process improvements.
- Operate as a peer, not a manager — lift standards through quality of work and direct feedback.
Innovation & AI
- AI as Your Default Toolchain: You reach for your AI-enabled IDE, LLM-based assistants, and AI-powered static analysis before anything else — not as a shortcut, but because better tools produce better outcomes. You don't write code you can automate reviewing.
- Integration Workflows, Augmented: You actively prototype and deploy AI/LLM services inside integration solutions — summarization, document parsing, intelligent transformation, synthetic test data generation.
- Advance automation with AI-assisted code review and LLM-based development platforms to accelerate delivery and lift code quality across the team.
Ways of Working
- The best engineers here don't wait to be told what to do next. They already know. You set direction, track your own commitments, and communicate proactively — without a layer between you and the client.
- WIP stays at ≤2 concurrent workstreams. You know what's at risk before your teammates do.
- If you've always been three steps ahead of your own deadlines, you'll feel right at home.
Required Qualifications
- Consulting Services Experience: 3–5+ years delivering integration programs for external clients — leading discovery/estimation, shaping SOWs, managing stakeholders from exec to dev, and owning delivery KPIs. This is non-negotiable. Internal IT delivery experience does not substitute.
- Client-Facing Ownership: Proven track record of managing client relationships through the full engagement lifecycle — including difficult scope and change-order conversations that preserve both trust and margin.
- API & Microservices Architecture: Expert in designing, implementing, and maintaining distributed, scalable API-led solutions using MuleSoft and industry-standard patterns.
- MuleSoft Platform Mastery: Advanced hands-on with Anypoint Platform, including DataWeave 2.x, CloudHub 2.0, Runtime Fabric, Flex Gateway, and Anypoint MQ.
- Autonomous Execution: Demonstrated ability to self-govern in flat, PM-free consulting environments — independently scoping, prioritizing, and delivering without hand-holding. If you've only worked in highly structured orgs, be honest with yourself about this one.
- AI/LLM Tools & Automation: You don't just tolerate AI tools — you seek them out. Cursor, LLM-based assistants, AI-powered static analysis — these are in your daily rotation, not your LinkedIn bio.
- DevOps, CI/CD & Automation: Strong experience with CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins), containerization (Docker/Kubernetes), and cloud-native deployment strategies.
- Security & Integration Standards: Advanced knowledge of RAML/OAS, OAuth2, JWT, TLS, and encryption best practices.
- Programming Proficiency: Skilled in Java and Node.js, with the ability to refactor legacy codebases into clean, maintainable solutions.
- MuleSoft Certifications: MuleSoft Certified Developer – Level 1 required; Architect or Integration Professional certifications strongly preferred.
Preferred/Bonus
- Experience integrating Salesforce, AWS, or other SaaS/ERP platforms.
- Familiarity with event-driven architectures (Kafka, Pub/Sub).
- Hands-on experience or strong interest in AI/ML pipeline design or integration.
Transform Your Career — the AI-First Way
At Green Irony, you…
- Take full ownership of your work—proactively solve problems and drive deliverables to completion.
- Relentlessly pursue outcomes, measuring success by delivered value, not just output.
- Solve complex problems with practical, innovative solutions.
- Communicate directly, transparently, and with positive intent—focusing on clarity, not politics.
- Grow continuously—mentoring, learning, and automating to expand your impact.
Benefits Snapshot
- Competitive salary + performance bonus
- Medical, dental, and vision coverage
- 401(k) with generous company match
- Flexible PTO and remote-first work environment
- Annual professional development budget (certifications, conferences, AI tools)
- Equipment stipend
Equal Opportunity, Zero BS
Green Irony is an equal opportunity employer committed to building an inclusive team where diverse voices drive better outcomes.
We evaluate all qualified applicants without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, veteran status, disability, or any other protected classification—because the only bias we tolerate is toward delivering excellent work.
Ready to apply?
Apply to Green Irony