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Added 8 hours ago
DevOps Engineer
Jobgether
Remote, United States
As your skills and security eligibility develop, you will have opportunities to take on more advanced responsibilities involving Kubernetes, GitLab CI/CD, AWS, Databricks, and enterprise…
Added 14 hours ago
Database Analyst (Information Systems Specialist 7)
Oregon Health Authority
Remote, United States
…monitoring, maintenance, performance tuning, backup and recovery, security, and troubleshooting of Microsoft SQL Server or comparable relational database management systems in on-premises,…
Added 16 hours ago
AI/ML Software Engineer
ASG
Remote, United States
…and data platforms that unlock new value from data. The AI/ML Engineer will lead and contribute directly to projects such as internal LLM applications, data pipelines, ML-powered product…
Added 16 hours ago
Database Administrator (Fully Remote)
MRIoA
Remote, United States
Snowflake/Databricks equivalent), Security+, or ITIL Foundation.
Added 16 hours ago
GI
Data Analyst (Dashboard Developer)
Guidehouse Inc.
Remote, United States
- $68,000 to $113,000 USD / year
Leading and reviewing data cleaning scripts using tools such as Databricks, SQL, and Python.
Added 17 hours ago
Site Reliability Engineer
Humana Inc.
Remote, United States
…solutions using technologies such as Python, Angular, SQL, Databricks, SSIS, and enterprise AI gateways for secure integration with AI models. This role requires a strong software…
Added 19 hours ago
Solutions Architect - Retail
Databricks
Remote, United States
Databricks certifications (Data Engineer, ML, Platform)
Added 19 hours ago
TL
AI Infrastructure Engineer [Tooling]
Tessera Labs
Remote, United States
- $200,000 to $230,000 USD / year
…across platforms like SAP, Salesforce, Workday, Snowflake, Databricks, and…
Added 19 hours ago
TL
AI Infrastructure Engineer [Senior]
Tessera Labs
Remote, United States
- $200,000 to $290,000 USD / year
As an AI Infrastructure Engineer, you’ll design and own production-grade AI agent infrastructure that supports Tessera’s AI systems across multiple cloud providers. You’ll work on…
Added 20 hours ago
AS
Lead Data/AI Engineering
AT&T Services, Inc.
Remote, United States
- $158,200 to $237,400 USD / year
Databricks Application Development: Design, build, deploy, and support production‑grade Databricks applications that connect enterprise data, AI capabilities, and business workflows, using…
Added 20 hours ago
Solutions Architect - Retail
Databricks
Remote, United States
Databricks certifications (Data Engineer, ML, Platform)
Added 20 hours ago
Staff Security Software Engineer
General Motors LLC
Remote, United States
We're looking for a seasoned Security Software Engineer to join our IAM team (Identity Access Management) to help develop, architect and advance our suite of applications and services. You…
Added 20 hours ago
TL
Solution Architect Product Engineer/AI
The LaunchCode Foundation
Remote, United States
- $195,000 to $210,000 USD / year
Hands-on experience with Azure AI, Azure OpenAI, Databricks, ML/data pipelines, event-driven architectures, and scalable data systems.
Added 1 day ago
L
Architect, Data Engineer (SAP + Databricks)
Lovelytics
Remote, United States
- $150,000 to $215,000 USD / year
…ML, and Cloud Migration & Modernization - all delivered on Databricks, with deep partnerships across AWS, Azure, and GCP. To date, we've delivered over $2B in business value for Fortune 500…
Added 1 day ago
Solutions Architect - Games
Databricks
Remote, United States
Databricks certifications (Data Engineer, ML, Platform)
Added 1 day ago
Solutions Architect - Games
Databricks
Remote, United States
Databricks certifications (Data Engineer, ML, Platform)
Added 1 day ago
Principal AI Engineer
Mom's Meals
Remote, United States
The Principal AI Engineer serves as Mom's Meals' lead AI consultant and technical expert, partnering with business leaders to identify opportunities, design innovative AI solutions, and…
Added 1 day ago
BV
AI Data Platform Engineer
Bright Vision Technologies
Remote, United States
- $100,000 to $150,000 USD / year
We are seeking a AI Data Platform Engineer to define and lead the architecture of our enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers.…
Added 1 day ago
J
Senior Model Based Systems Engineer
Jobgether
Remote, United States
- $89,100 to $148,200 USD / year
…steps. Our partner is looking for a Senior Model Based Systems Engineer based in the United…
Added 1 day ago
Principal Engineer, Integrated Product Analytics Innovation Lead (Remote)
RTX
Remote, United States
Added 1 day ago
A
Data Solution Engineer
Aretum
Remote, United States
- $110,000 to $125,000 USD / year
…solutions to our customers across defense, civilian, and homeland security sectors. Our teams work at the intersection of strategy, technology, and transformation, helping agencies solve…
Added 1 day ago
AI/ML & MLOps Engineer (SME)
DecisionPoint | Cortek
Remote, United States
DecisionPoint seeks an AI/ML & MLOps Engineer to lead the architecture, deployment, monitoring, automation, and governance of production machine learning capabilities supporting the…
Added 1 day ago
AI/ML & MLOps Engineer (Senior)
DecisionPoint | Cortek
Remote, United States
DecisionPoint seeks a Senior AI/ML & MLOps Engineer to build, deploy, monitor, maintain, and govern production machine learning capabilities supporting the USMEPCOM ENLIST program.
Added 1 day ago
A
Senior Data Solution Engineer
Aretum
Remote, United States
- $115,000 to $145,000 USD / year
…solutions to our customers across defense, civilian, and homeland security sectors. Our teams work at the intersection of strategy, technology, and transformation, helping agencies solve…
Added 1 day ago
A
Senior Data Solution Engineer
Aretum
Remote, United States
- $115,000 to $145,000 USD / year
…solutions to our customers across defense, civilian, and homeland security sectors. Our teams work at the intersection of strategy, technology, and transformation, helping agencies solve…

Arctiq

Solution Engineer, Data & AI

Remote, United States

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Job details

Posting language: English
Posted: Oct 26, 2026

Original job description

Company Overview:

Arctiq is a global, intelligence-driven technology services company delivering professional and managed services across Hybrid Cloud Infrastructure, Networking & Connected Experiences, Cybersecurity, Data & AI, Autonomous Operations & Intelligence, and Enterprise Service Management. We help organizations operate, secure, and modernize complex environments by unifying infrastructure, networking, data, security, automation, and observability under a single, integrated operating model. Our work focuses on helping customers reduce operational friction, improve resilience, and make better, faster decisions as their environments evolve. Arctiq builds on decades of industry expertise and a customer-centric ethos to deliver exceptional value to clients across diverse industries.

Position Overview:

The Solution Engineer, Data & AI is a hands-on builder who designs, delivers, and operates production-grade data and AI solutions. You will join a team of engineers who bring real software engineering discipline to data work - version control, automated testing, CI/CD, infrastructure as code, and observability are how we work, not afterthoughts. We also expect our engineers to embrace agentic engineering, using tools like Claude Code to dramatically accelerate how software gets built without compromising quality.

Depending on business need and your strengths, you will be aligned to one of two paths:

Path 1 - Client Delivery: Support delivery of fixed-price, outcome-based data and AI projects for clients across a wide range of industries and problem domains, on Azure, AWS, and GCP. In a fixed-price model, engineering quality and delivering within agreed scope directly affect client outcomes and project margin.

Path 2 - Internal Data & Analytics: Bring order to our internal data on Azure Databricks - integrating, cleaning, and modelling data from our business systems so the organization has trusted analytics and reporting and helping automate core business processes such as quote-to-cash.

Both paths share the same technical foundation, and engineers may move between paths over time as priorities and interests evolve.

Responsibilities:

Data Pipeline Engineering

• Design, build, and maintain reliable, scalable data pipelines for batch and streaming workloads

• Apply proven lakehouse architecture patterns, with clear data contracts and well-managed schema evolution

• Build data quality checks, testing, and monitoring into every pipeline from day one

Data Modelling & Analysis

• Design analytical data models that reflect business requirements and perform at scale

• Profile, explore, and analyze data to validate assumptions, surface quality issues, and share meaningful insights with stakeholders

• Apply sound data governance practices so data assets are secure, traceable, and discoverable

AI & Machine Learning Engineering

• Build, train, and evaluate machine learning and generative AI solutions - from classical ML to LLM-based and agentic applications

• Establish rigorous evaluation approaches tied to clear, business-aligned success criteria

• Take models from experimentation to production, ensuring they are reliable, observable, and maintainable

MLOps & DevOps

• Build and maintain CI/CD pipelines for code, data, and models

• Manage cloud and platform resources through infrastructure as code

• Implement full model lifecycle management - versioning, deployment, monitoring, drift detection, and retraining

• Champion engineering best practices across the team: code reviews, branching strategies, automated testing, and documentation

Agentic Engineering

• Use agentic coding tools (e.g., Claude Code) as a core part of your daily workflow to accelerate design, development, testing, documentation, and refactoring

• Provide AI agents with effective context through clear specifications, project instructions, and reusable workflows

• Apply rigorous review, testing, and validation to AI-generated code - you own the quality of what ships, regardless of who or what wrote it

• Share effective agentic workflows with the team and help codify them into repeatable practices and accelerators

Path 1 - Client Delivery

• Deliver engineering workstreams on fixed-price client engagements, from technical discovery through outcome acceptance

• Work across client environments on Azure, AWS, and GCP, adapting patterns to each client’s cloud, security model, and constraints

• Partner with Architects and your Engineering Manager to deliver solutions within agreed scope, timeline, and commercial constraints

• Participate in client workshops, demos, and technical working sessions, building credibility with client technical teams

• Identify scope creep, technical risks, and blockers early - and raise them promptly and constructively

• Leave clients better off: document solutions clearly, transfer knowledge, and help build client-side capability

• Contribute to reusable accelerators, templates, and patterns that make future engagements more predictable

Path 2 - Internal Data & Analytics

• Integrate data from our core business systems (e.g., CRM, PSA, finance/ERP, HR) into our Azure Databricks environment

• Clean, reconcile, and standardize messy internal data - resolving duplicates, aligning definitions across systems, and establishing a single source of truth for key entities such as customers, projects, contracts, and revenue

• Coordinate with internal teams to identify, prioritize, and resolve data quality issues at the source, and put processes in place to prevent them from recurring

• Build trusted, well-documented data models that power internal analytics, KPIs, and executive and operational reporting

• Partner with Finance, Sales, Operations, and leadership to understand reporting needs and translate them into reliable data products

• Help design and automate quote-to-cash workflows, connecting data and handoffs from opportunity through quote, contract, delivery, invoicing, and collections

Qualifications:

• 4+ years in software and platform engineering, including meaningful time on a collaborative software development team

• Hands-on experience building production data and ML solutions in the cloud

• Strong, demonstrable experience with the Databricks platform in production environments

• Practical experience using agentic coding tools to accelerate software development - with examples of how it has changed the way you work

Technical Skills

Software Engineering & DevOps

• Strong proficiency in Python and SQL

• Solid software engineering fundamentals: Git workflows, code review, unit and integration testing, modular design

• Hands-on experience with CI/CD tooling and infrastructure as code

• Comfortable with containerization, environment management, and automated deployment

Cloud Platforms

• Working knowledge of all three major clouds - Azure, AWS, and GCP - with deep hands-on experience in at least one

• Understanding of how data platforms are deployed and integrated on each cloud, including storage, identity, networking, and security

• Familiarity with each cloud’s native data and AI services and when to use them alongside Databricks

Databricks

• Deep, hands-on experience across the Databricks platform, including data engineering, governance, and ML/AI capabilities

• Experience deploying and managing Databricks solutions using software engineering and DevOps best practices

Data Engineering & Modelling

• Proven ability to design and build scalable batch and streaming pipelines

• Strong data modelling skills across dimensional and modern lakehouse patterns

• Experience with data quality frameworks, testing, and observability

AI / ML & MLOps

• Practical experience building, evaluating, and deploying ML models to production

• Experience with generative AI patterns such as retrieval-augmented generation, agents, and LLM evaluation

• Strong MLOps practices across the full model lifecycle

Agentic Engineering

• Hands-on proficiency with agentic development tools such as Claude Code

• Ability to decompose work, write clear specifications, and manage context so agents produce high-quality results

• Sound judgment on where AI-assisted development adds leverage and where it introduces risk, with a disciplined approach to reviewing and testing its output

Arctiq is an equal opportunity employer. If you need any accommodations or adjustments throughout the interview process and beyond, please let us know. We celebrate our inclusive work environment and welcome members of all backgrounds and perspectives to apply.

We thank you for your interest in joining the Arctiq team! While we welcome all applicants, only those who are selected for an interview will be contacted.

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