What you’ll do

Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:

• Install, configure, and maintain AI platform and tools.
• Design, deploy, and operate infrastructure supporting ML and LLM workloads.
• Build, containerize, and deploy AI services using Docker.
• Build and maintain Machine Learning CI/CD pipelines for training, testing, and deployment.
• Deploy and manage AI services across cloud and on-prem environments.
• Automate infrastructure provisioning using Terraform and Infrastructure-as-Code best practices.
• Monitor system performance, reliability, and scalability of AI platforms.
• Implement observability for agentic AI systems to ensure reliability, transparency, and debuggability.
• Perform regular security updates, patching, access control, and vulnerability remediation.
• Integrate AI tools with APIs, data platforms, and internal systems.
• Research, evaluate, and prototype new AI, LLM, and MLOps tools.
• Troubleshoot infrastructure, data, and deployment issues.
• Research, test, and prototype emerging AI technologies.
• Document system architecture, deployment processes, and operational runbooks.

Location & Travel Expectations:

• This role is based out of the Scout Motors corporate headquarters in Charlotte, NC.
• This role requires 4-5 days per week in the office, with regular in-person meetings and events. 
• Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.

What you’ll bring 

We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring: 

• Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
• 7+ years Practical experience with LLM platforms, LLMOps, and MLOps.
• Experience deploying and maintaining AI or data platforms in production.
• Hands-on experience with AI/automation tools.
• Experience designing and orchestrating agentic automation workflows.
• Strong experience with Terraform and Infrastructure-as-Code.
• Proven experience deploying applications using Docker (Docker files, image optimization, container lifecycle).
• Expertise with cloud platforms such as AWS.
• Expertise with CI/CD tooling (GitHub Actions, GitLab CI).
• Strong Knowledge of Kubernetes and orchestration.
• Solid understanding of networking.
• Experience supporting high-availability, production AI systems.
• Scripting skills (Python, PySpark, Bash).
• Knowledge of security best practices, patch management, and access controls.
• Collaborate with engineering, data, and product teams to support AI initiatives.
• Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
• Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options.
• A teaching and coaching approach to guiding engineers and teams in approaches.
• Minimum of High School Diploma, GED or equivalent required for all roles at Scout Motors, Inc.

What you'll gain

The benefits of joining Scout include the chance to build products and a company from the ground up.  This is a chance to create something new and lasting – with an iconic brand at its foundation.  In addition, Scout provides competitive compensation and benefits to support your physical, mental, and financial wellbeing. Program specifics are detailed in company policies and employee benefit guides, select highlights:

• Competitive insurance including:
  • Medical, dental, vision and income protection plans
• 401(k) program with:
  • An employer match and immediate vesting
• Generous Paid Time Off including:
  • 20 days planned PTO, as accrued
  • 40 hours of unplanned PTO and 14 company or floating holidays, annually
  • Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
  • Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave

Pay Transparency

This is a full-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to the candidate's skills and experience. The annual performance bonus program is preset and not candidate dependent.

Initial base salary range = $140,000.00 - $170,000.00

Internal leveling code: IC8

The Solutions Engineer Team

We believe Solutions Engineers at Okta are involved in all stages of the customer’s digital transformation.  Solutions Engineers are experienced in using presentations, email, phone, and social media to connect with customers virtually and in person. We are looking for great teammates who can build and deliver sales presentations and customized product demonstrations to educate Okta’s Customers (from developers to product managers to C-level executives) on best practices throughout their cloud security technology journey. 

We believe Okta’s Solutions Engineers empathize with Customers and quickly discern their true technical needs by asking detailed, clarifying questions while presenting solutions that specifically address those needs. Okta Solution Engineers have the rare combination of technical acumen and business insight; in a career where you can utilize both. As a Solutions Engineer at Okta, you will further develop each of these skills by advising a diverse set of customers on the value they will gain by using Okta’s Identity Platform.

The Solutions Engineer Opportunity

Reporting to the Senior Manager, Solutions Engineers, this Senior Solutions Engineer (Okta) will partner with Commercial Account Executives. As a Senior Solutions Engineer at Okta, you will be the technical lead in all stages of the customer lifecycle. You will focus on delivering customer value by aligning customer requirements to business results enabled by Okta solutions. You will contribute to account and opportunity strategies and, collaboratively, demonstrate the value of Okta solutions through presentations, whiteboard sessions, and proof-of-concept demonstrations.

What You’ll Do

As a Senior Solutions Engineer, you’ll be a strategic technical expert for a customer-facing sales team. You'll use your skills to:

• Work alongside the Corporate/Expansion (employee size 300-1249) sales team as the technical and domain expert of a customer-facing sales team to help Customers understand the value of Okta’s solutions
• Serve as a technical advisor: Partner with the sales team to educate customers on Okta’s identity solutions and demonstrate their value.
• Solve customer challenges: Understand customer needs and provide tailored product demonstrations to show how our solutions can solve their business problems.
• Lead technical engagements: Answer product and technical questions, and plan and deliver complex Proofs of Concept (POCs) by collaborating with other Okta engineering teams.
• Drive product and knowledge growth: Share customer feedback with our product teams to influence future enhancements and contribute to the team's knowledge by sharing best practices and reusable assets.
• Stay ahead of the curve: Keep up with competitive analysis and market differentiation to better position Okta.
• Support company events: Represent Okta at marketing events, including conferences, user groups, and trade shows.

What You’ll Bring

• Experience: 8+ years of experience in pre-sales engineering and solution selling, with a strong background in Enterprise account segments.
• Technical Acumen:
• Deep understanding of identity protocols (e.g., SAML, OIDC, OAuth, FIDO, Passkeys, SCIM, LDAP).
• Working knowledge of cloud platforms like AWS, Azure/Entra, and GCP.
• Experience with REST APIs and SDKs.
• Hands-on experience in one or more of the following: front-end web development, back-end development, scripting (Bash, PowerShell), or DevOps (Docker, Kubernetes).
• Understanding of identity-related cybersecurity topics (e.g., phishing, MFA bypass attacks, privilege escalation).
• Communication & Presentation Skills: The ability to simplify complex technical concepts and deliver compelling presentations to diverse audiences, from developers to C-level executives. You should be skilled at diagramming user journeys and complex architecture.
• Strategic Mindset: Proven skills in territory management, including building pipelines and collaborating with sales counterparts.
• Travel: Ability to travel up to 25% of the time.
• A bachelor's degree in Engineering, Computer Science, MIS, or a comparable field is preferred.

Bonus Skills (Ideally, You Have)

• Experience in the IAM space
• Hands-on knowledge of Identity Governance (IGA) or Privileged Access Management (PAM) solutions.
• Practical experience with Windows Server, Active Directory, LDAP, and Federation services.

You might also have (not mandatory):

• AI & Emerging Tech: Expertise with Agentic AI and LLM-based workflows. You understand the use cases for AI agents, both internal and external, and have familiarity with MCP servers.
• Diagramming experience for user journey flows, complex architecture diagrams, etc.

#LI-Remote

#LI-CM

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The Solutions Engineer Team

We believe Solutions Engineers at Okta are involved in all stages of the customer’s digital transformation.  Solutions Engineers are experienced in using presentations, email, phone, and social media to connect with customers virtually and in person. We are looking for great teammates who can build and deliver sales presentations and customized product demonstrations to educate Okta’s Customers (from developers to product managers to C-level executives) on best practices throughout their cloud security technology journey. We believe Okta’s Solutions Engineers empathize with Customers and quickly discern their true technical needs by asking detailed, clarifying questions while presenting solutions that specifically address those needs. Okta Solution Engineers have the rare combination of technical acumen and business insight; in a career where you can utilize both. As a Solutions Engineer at Okta, you will further develop each of these skills by advising a diverse set of customers on the value they will gain by using Okta’s Identity Platform.

The Solutions Engineer Opportunity

Reporting to the Senior Manager, Solutions Engineering, the Solutions Engineer is a functional business consultant who will partner with Commercial Account Executives and have  a passion for technology and the advanced ability to develop, position, and demonstrate product-specific solutions during sales cycles, while achieving quarterly and annual sales goals for an assigned territory.

What you’ll be doing

• Work alongside the Corporate/Expansion (employee size 300-1249) sales team as the technical and domain expert of a customer-facing sales team to help Customers understand the value of Okta’s solutions
• Understand customer challenges and business issues, and provide product demonstrations to align our solutions with customer needs
• Answer product feature and technical questions from customers, partners, and Okta colleagues
• Plan and deliver Proof Of Concepts for customers who have more complex use cases, collaborating with other Okta engineering teams as needed
• Provide feedback to product management about product enhancements that can address customer needs and provide additional value
• Share and learn best practices and reusable assets with other Solutions Engineers to enhance the quality and efficiency of the team
• Stay current on competitive analysis and market differentiation
• Support marketing events, including executive briefings, conferences, user groups, and trade shows

What you’ll bring to the role

• 5+ years of pre-sales engineering experience, selling SaaS products.
• A passion to serve the Customer, demonstrated in a customer-facing role, such as consulting or support, but ideally in a pre-sales capacity.
• An ability to quickly communicate complex ideas around a technical topic, ideally on the fly, using a whiteboard.
• Experience with at least one standard network security protocol. (eg. OAuth, OAuth2, SAML, LDAP)
• Hands-on experience in one or more of the following areas: web (JavaScript, HTML, frontend frameworks) development, mobile (iOS, Android) development, backend (Java, C#, Node.js, Python, PHP, Ruby) development, IP-based real-time communications.
• An understanding of core security concerns within a typical application. (password hashing, SSL/TLS, encryption at rest, XSS, XSRF)
• Exceptional communicator.
• Confidently dispensing knowledge to highly-skilled and experienced audiences.
• Typically, 25% travel.
• A bachelor's degree in Engineering, Computer Science, MIS, or a comparable field is preferred.

You might also have (not mandatory):

• AI & Emerging Tech: Expertise with Agentic AI and LLM-based workflows. You understand the use cases for AI agents, both internal and external, and have familiarity with MCP servers.
• Diagramming experience for user journey flows, complex architecture diagrams, etc.
• Experience in the IAM space

#LI-Remote

#LI-CM

P9259_3401412

POSITION SUMMARY: 

Assist direct Manager in overseeing and leading clinical data abstractors and related operations. Partner with the Lead Quality Abstractor, and the team’s software engineers and data management specialists to operationalize end-to-end abstraction, clinical data management workflows and activities, and lending technical support. Serve as the first line of communication and point of escalation amongst the data abstractors. 

PRIMARY RESPONSIBILITIES:

• Front-line Staff Support: Serve as the primary liaison and initial point of escalation for all abstraction/team-related issues, questions, and concerns.

• New Hire Onboarding and Training: Lead training new abstractors and provide ongoing guidance until released into production level activities by supporting the development and implementation of training workflows.  

• Mentoring and Subject Matter Expertise (SME): Provide ongoing clinical guidance and mentorship to existing abstraction team members- fostering professional development. Support maintaining high standards of quality and productivity by evangelizing the utilization of standard of care guidelines. 

• Technical Support: 

  • Lead ongoing clinical and medical guidance to engineering, data management specialists, and technical staff to ensure the development of bug-free data for systems such as Electronic Data Capture Systems (ECDs), applications, and workflows. 

  • Apply Medical Coding and Classification skills to support the creation of data standardization and harmonization rules to ensure clinical data are encoded into machine readable data in one common database schema.

  • Apply Data Management knowledge (e.g., CGDM, GCP) and skills to support establishing logical relationships between clinical events within database schemas and logical rules for ensuring data are accurate, legible, contemporaneous, original, attributable, complete, and consistent for end-to-end ETL workflows. 

  • Apply Technical Skills to translate abstraction and encoding requirements to technical product requirements to support prompt engineering and design activities for all AI and LLM initiatives.  

• Data Abstraction: Advanced level review, interpretation, abstraction and data encoding. Less than 5% of patients require quality review. 

• Quality Assurance and Control: Apply and lead efforts in resolving complex or ambiguous data abstraction questions, ensuring consistent and adherence to established protocols and standards for utilizing real-world data for research, quality monitoring, and regulatory reporting using technical and analytical software such as running MACROs and using Excel/Google Sheets functions and formulas. 

• Protocol Adherence: Support developing and ensuring strict adherence to all project and research protocols, institutional review board requirements, HIPAA regulations, data management best practices (e.g., DAMA, SCDM, ACRP, and SOCRA), and organizational policies regarding patient privacy and data security. 

• Reporting: Track, analyze, and report on key abstraction and staff level metrics to support the assessment of team performance and identify areas for process improvement by gathering and structuring KPIs using software such as Excel, googlesheets Pivot tables, formulas, and functions.                                                                                

• Process Improvement: Collaborate with cross-functional teams to effectively operationalize new abstraction activities, including the rollout of new protocols, standard operating procedures, and policies and technology platforms. 

• Daily Operations: Support direct manager in daily coordination of the clinical data abstraction team's activities and workload distribution.

• Conferences and Certifications: Maintenance of all relevant clinical or technical licensures. Attend conferences relevant to role and clinical field. 

• Other duties and responsibilities to be performed as assigned. 

QUALIFICATIONS: 

• Clinical Background: U. S. licensed Nurse, PA-C, NP, or DNP is required with a Master’s degree in health sciences. Strong understanding of medical terminology, disease processes (especially cancer), standard clinical workflows, and genetic testing.

• Clinical Experience: Minimum of 5-6 years of experience in clinical data abstraction and medical records review, preferably in cancer, women’s health, rare diseases. 

• Lead Experience: Minimum of 2-3 years of direct experience supervising staff or providing team lead support to senior level management. 

• Quality and Compliance: Demonstrated commitment to data integrity, quality control processes, and adherence to HIPAA and other data privacy regulations.

• Technical Proficiency: Proficient with Microsoft Office Suite or Google Suite, creating pivot tables, creating reports, data analysis, and using  systems or databases common in data abstraction, research, or clinical data management.

• Certifications/Industry Expertise: CCDM, CCRP, ACR-P, or CRA preferred.

• Communication: Excellent written and verbal communication skills, with the ability to effectively collaborate with clinical and non-clinical teams.

• Autonomy: Proven ability to work independently, manage time effectively, prioritize and organize tasks, and meet strict productivity and quality deadlines

• General Expertise:

  • Possess a high level of initiative and self-motivation.

  • Team player; can navigate supporting highly visible projects and tasks. 

  • In-depth attention to detail and a fast learner. 

  • Responding to shifting priorities and changes.

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

Target RWE is seeking a Senior AI/ML Engineer to join our Technology team and help shape the next generation of real-world evidence solutions. In this hands-on role, you will design, develop, and deploy scalable machine learning systems — with a particular focus on large language model (LLM) applications. These systems enable our researchers, statisticians, and clinical teams to extract deeper insights from complex healthcare data. Your work will directly support Target RWE’s mission of advancing clinical research and informing better healthcare decisions at scale.

This is a highly collaborative position. You will partner closely with software engineers, data scientists, research scientists, and product managers to build high-performing, reliable, and scalable ML-native platforms. You will also serve as a technical leader within the Engineering team, helping cultivate a strong ML engineering culture and staying at the forefront of rapidly evolving AI technologies. This role reports to the Director of Engineering.

This is a role for someone who thrives at the intersection of cutting-edge AI research and production-grade engineering. The right fit is someone who can translate state-of-the-art methods into durable, enterprise-ready systems while understanding the requirements of clinical research. This is an exceptional opportunity for someone excited about applying AI to transform how clinical evidence is generated and used.

What You’ll Do

• Design, develop, and deploy scalable ML software systems to address large-scale analytical challenges in healthcare and real-world evidence generation.
• Translate state-of-the-art LLM research — both internally developed and from the broader research community — into production-ready solutions that deliver measurable value for our customers and internal teams.
• Work with complex, large-scale, real-world clinical data (structured and unstructured) in a cloud-based environment, ensuring quality and reliability across the data pipeline.
• Develop methods and features to ensure high-quality production model results, including drift detection, performance degradation monitoring, and observability tooling.
• Collaborate with software engineers, research scientists, and product teams to build ML-native enterprise platforms, ensuring scalability, efficiency, and reliability at every layer.
• Ensure robust monitoring, logging, and error handling for all deployed ML systems.
• Stay current on the latest advancements in machine learning and AI, and proactively identify opportunities to apply relevant innovations to Target RWE’s platform.
• Cultivate a strong ML engineering culture across the organization, contributing to best practices, code reviews, documentation, and technical mentorship.
• Partner with cross-functional stakeholders to translate complex technical concepts and model outputs into clear, actionable insights for non-technical audiences.

What You’ll Bring

• 5+ years of experience in backend and cloud platform software development, with the flexibility to traverse the stack when necessary.
• Fluency in Python.
• Strong familiarity with modern ML and LLM techniques, frameworks, and tooling.
• Demonstrated experience developing and maintaining high performing, scalable, data-centric enterprise software products.
• Strong problem-solving skills and meticulous attention to detail in technical design, implementation, and documentation.
• Excellent communication skills, with the ability to clearly articulate complex technical concepts to non-technical stakeholders.
• Collaborative team player who thrives in a cross-functional environment alongside engineers, researchers, and product managers.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.

Nice to Have 

• Experience in 0-to-1 development of end-to-end ML systems, including design, training, inference, deployment, and monitoring.
• Hands-on experience with LLMs in production environments, including fine-tuning, prompt engineering, or retrieval-augmented generation (RAG).
• Experience building the plumbing necessary for RAG-based approaches, including data vectorization, vector stores, and various search methodologies.
• Background in healthcare, clinical informatics, or life sciences, with familiarity with real-world clinical data sources (EHR, claims, registries).

If you are ready to be part of a team where your work truly matters - where your expertise is valued, your growth is supported and your contributions help shape the future of healthcare, Target RWE is the place for you. We’re building something meaningful together, and we’d love for you to be a part of it. 

What we offer you

• Hybrid work — 3 days/week in our brand-new office!
• Comprehensive health, dental, and vision for you and your family
• 401(k) with company match
• Generous PTO and company holidays
• Paid parental leave 

At Target RWE, our mission is driven by a deep commitment to people—whether it’s the patients we serve, the partners we collaborate with, or the dedicated team members who power our work. As a purpose-driven organization, we leverage real-world data to advance clinical research and inform better healthcare decisions. We foster a collaborative environment where every voice is heard, every idea has an impact, and every contribution helps improve lives. If you're seeking a place where your work truly matters, join us to advance science. 

We are seeking a talented Data Engineer to join our Technology team. In this role, you will develop, create, and modify computer application software and databases to drive operational efficiency and improve business processes. You will collaborate closely with stakeholders to analyze user needs, design custom software solutions, and implement scalable, reliable applications that support Target RWE’s mission.

What You’ll Do

• Design and implement data pipelines and software solutions that promote operational efficiency and scalability.
• Analyze business requirements and work with stakeholders to translate needs into technical solutions.
• Write clean, maintainable code primarily in Python, with a strong emphasis on SQL for data manipulation and transformation.
• Support and optimize cloud-based data infrastructure (AWS preferred).
• Develop and modify databases to support internal applications.
• Collaborate with operations and product teams to support deployment, testing, and maintenance.
• Help troubleshoot production issues and contribute to ongoing improvement efforts.
• Stay up to date on relevant tools, technologies, and best practices.

What You’ll Bring

• 3+ years of software development experience, ideally in data engineering, data platform development, or backend systems.
• Strong proficiency in SQL and Python.
• Experience with cloud platforms (AWS, GCP, or Azure) and working in cloud-native environments.
• Familiarity with version control and CI/CD tools (e.g., GitLab, GitHub Actions).
• Strong problem-solving and communication skills.
• Ability to work independently and manage tasks with moderate supervision.

Nice to Have 

• Experience working with or developing machine learning pipelines or models.
• Exposure to Generative AI or LLM frameworks (e.g., Langchain, LangGraph).
• Knowledge of distributed computing concepts or tools (e.g., Spark, Dask).
• Background in healthcare, life sciences, or clinical data.
• Bachelor’s degree in computer science, engineering, or a related field (or equivalent practical experience).

If you are ready to be part of a team where your work truly matters - where your expertise is valued, your growth is supported and your contributions help shape the future of healthcare, Target RWE is the place for you. We’re building something meaningful together, and we’d love for you to be a part of it. 

What we offer you

• Hybrid work — 3 days/week in our brand-new office!
• Comprehensive health, dental, and vision for you and your family
• 401(k) with company match
• Generous PTO and company holidays
• Paid parental leave 

Role Description

• As an Senior Value Engineer specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

The Team

Celonis makes processes work for people, companies, and the planet. As the Celonis Services organization, we are the strategic implementation consulting & transformation arm of a unified Customer Organization aligned to four core mandates:

1. Make Celonis Business Critical: Transform the platform into the central nervous system of our customers’ operations.
2. Scale Customer Health: Drive full platform adoption to ensure long-term value and stability.
3. Focus on High-Value Activities: Prioritize complex, high-impact technical work that moves the needle for Focus & Strategic customers.
4. Empower Career Growth: Foster an environment where every Celonaut owns customer success while accelerating their own professional trajectory.

We deliver production-ready Celonis Platform implementations that drive measurable top, bottom, and green-line impact. Moving beyond “point-in-time” analysis, we utilize a Discover-and-Build approach to solve the world's most complex operational challenges.

In close partnership with Value Engineering, we perform data-driven discovery to validate business hypotheses against real-world data. We then build and deploy operational, AI-enriched solutions on top of the Celonis Platform that automate decisions and optimize workflows at an enterprise scale.

We don't just implement AI for our customers; we live it. Our project delivery lifecycle is accelerated by state-of-the-art AI augmentation, allowing our consultants to focus on high-level, strategic problem-solving. By serving as the "eyes and ears" in the field, we maintain a continuous innovation loop with our Product & Engineering teams, ensuring our frontline learnings directly shape the future of the Celonis Platform.

The Role

You are an AI Deployment Architect (AIDA). You own the reality of scaling solutions within a customer's actual IT environment and productizing those results. Complementing your colleagues in Applied Value Engineers and Applied AI Engineering, who focus on pre-sales prototyping, you bridge the gap between "the art of the possible" and Business Critical, scaled solutions. As an AIDA, you steer account teams and customers toward AI use cases that are inherently scalable. You are not the primary implementer of these solutions. Instead, you steer the definition of the architectural vision for Consultants to execute and oversee delivery excellence. You remain hands-on for first-of-their-kind production solutions, eventually transitioning to an advisory capacity across a broad "book of work" within your assigned vertical.

The Work You’ll Do

• Advise and Safeguard Technical Implementations: Provide architectural oversight for concurrent deployments at Fortune 500 organizations. You act as the final technical authority, maintaining "project-ready" coding skills to troubleshoot and resolve critical production failures that block value realization.
• Architect AI-Enriched Solutions: Collaborate with pre-sales teams to transform experimental prototypes into robust, scalable enterprise applications. You then translate these successful deployments into standardized platform features by maintaining a tight feedback loop with Product and Engineering.
• Engineer Low-Latency Systems: optimize these AI-enriched solutions for high-throughput and minimal latency. You ensure the Celonis Platform handles near-real-time data integration without compromising the user experience of business-critical applications.
• Implement Eval-Ops & Automated Testing: Build rigorous evaluation pipelines to test LLM quality and reliability at scale. You move beyond manual spot-checks by institutionalizing automated benchmarks for model accuracy and safety.
• Deploy LLMOps & Lifecycle Governance: Design systems for continuous model monitoring, cost optimization, and performance tuning. You establish the frameworks for data privacy and compliance within the customer's actual IT environment.
• Troubleshoot Agentic Orchestration: Manage the complexity of multi-agent workflows where agentic activity is triggered by Celonis context and logged back to the platform. You ensure seamless hand-offs between agents and maintain the integrity of the full process loop.

 The Preferred Qualifications You Need

• Architectural Leadership: Proven experience designing and scaling innovative AI solutions within actual customer IT environments, moving these solutions from pilot to production.
• Advanced Technical Production: Ability to refactor experimental pilots for production-scale performance and a deep proficiency in Python for building enterprise-grade LLM-based solutions.
• Vertical Industry Expertise: In-depth understanding of complex business challenges within a specific industry vertical (e.g., Manufacturing, Life Sciences).
• Senior Stakeholder Management: Excellence in translating highly complex architectural concepts and AI governance frameworks into strategic roadmaps for C-suite stakeholders.
• Lifecycle Mastery: Experience in production-level acceptance testing, low-latency system design, and the management of ongoing LLM performance.
• Academic Excellence: Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, or a related quantitative field.

As a MuleSoft Architect, you won't be handed a ticket queue or a seat at someone else's table. You'll own the integration platform for our clients — end-to-end. That means standing up a production-ready API-led foundation, running an AI-first delivery program, and building the kind of trusted client partnerships that turn a single engagement into a long-term relationship. You set the architectural direction. The rest of the team follows your lead.

Location: Remote (US). Raleigh–Durham is a plus, not required.

Eligibility: Must live in the US and be authorized to work in the US; no sponsorship.

What You'll Own

You are the technical decision-maker for your client engagements — not a consultant waiting for sign-off.

• Integration Platform Ownership: Design the target-state API-led architecture (system/process/experience layers), define NFRs, govern standards, and publish reusable templates that teams actually use — not just reference.
• AI-First Program Leadership: Build the AI playbook. Create prompt and snippet libraries that accelerate design, mapping, and testing. Measure the before/after. Coach your team to adopt. Don't theorize — demonstrate.
• Delivery Accountability: Own milestones, scope, and LOE. Keep estimate variance ≤ ±15%. Communicate risks before anyone has to ask. Exec-ready updates go out weekly, without prompting.
• Presales Partnership: Lead discovery, shape solution architecture, and co-author SOWs with clear assumptions. You are the technical voice in the room — and you know how to make architecture land as a value narrative, not a tech briefing.
• Autonomous Execution: You track your own commitments. You surface risks before they surface you. If you've always been three steps ahead of your own deadlines, you'll feel right at home.

Key Responsibilities

Architecture & Platform

• Design API-led target state (system/process/experience), NFRs, and governance.
• Stand up CloudHub 2.0/RTF environments, networking, secrets, and promotion paths.
• Publish templates, policies, and error strategies in Exchange that set the delivery bar — and that teams actually use.

AI Program & Enablement

• Author a practical AI playbook + prompt/snippet library to accelerate design, mapping, and testing — safely.
• Measure cycle-time and quality deltas before and after. Show the gains. Coach adoption.

Delivery & Reliability

• Guide CI/CD strategy, config per environment, and zero-downtime/rollback patterns.
• Define SLOs, alerts, and dashboards. Build integrations that hit latency and accuracy targets.

Presales & Stakeholders

• Own discovery, solution architecture, and LOE/SOW development with clear assumptions.
• Translate architecture trade-offs into exec-ready options. Build presales assets that accelerate the next deal.

Documentation & Communication

• Write ADRs, API docs, and runbooks that make decisions legible and repeatable.
• Direct, no-fluff communication — always. If you can say it in three sentences, don't use ten.

Required Qualifications

• Architecture Experience (Required): 1+ year in a formal MuleSoft Architect role owning target state, decisions, and trade-offs — not just senior development duties.
• API & Integration Architecture: Expert-level API-led design on Mule 4/Anypoint with clean system/process/experience boundaries.
• 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.
• MuleSoft Platform Mastery: DataWeave 2.x, CloudHub 2.0, Runtime Fabric, Flex Gateway, Anypoint MQ; Exchange-driven reuse and policy governance.
• DevOps, CI/CD & IaC: Azure DevOps, GitHub Actions, Jenkins, Maven, Terraform; env promotion to CH2.0/RTF; blue/green + rollback strategies.
• Security & Standards: RAML/OAS, OAuth2/OIDC, JWT, mTLS/TLS, secrets, encryption — policy bundles baked into delivery, not bolted on after.
• Observability & SLOs: Anypoint Monitoring, Datadog, or Splunk; error budgets and actionable alerts.
• Cloud & Networking: AWS/Azure VPC/VPN, private spaces, NAT/DNS/certs; cost and performance trade-offs you can defend.
• Client-Facing Consulting Experience: You've worked at a consultancy or SI with direct client ownership. You run discovery, align stakeholders from exec to dev, contribute to LOE/SOW, and keep estimate variance ≤ ±15%. Internal IT delivery doesn't substitute.
• MuleSoft Certifications: MuleSoft Certified Platform Architect and/or MuleSoft Certified Integration Architect required.

Preferred / Bonus

• Experience leading presales end-to-end — discovery through signed SOW.
• Hands-on AI acceleration work with documented before/after delivery gains.
• Security and governance depth: policy-as-code, OAuth2/OIDC, mTLS, auditable standards teams actually follow.

Transform Your Career — the AI-First Way

At Green Irony, you…

• Take full ownership of your engagements — client, scope, delivery, and outcome.
• Relentlessly pursue measurable business value, not ticket throughput.
• Solve complex problems with practical, innovative solutions.
• Communicate directly, transparently, and with positive intent — clarity over 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.

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.