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Added 3 hours ago
Senior Azure Infrastructure Engineer
Jobgether
Remote, United States
The Senior Azure Infrastructure Engineer will design, implement, automate, and support secure, scalable, and resilient cloud infrastructure within an enterprise Azure environment. Working…
Added 2 days ago
VL
Sales Development Rep -SF Bay Area
vCluster Labs
Remote, United States
- $100,000 to $120,000 USD / year
…you are the frontline scout for the next generation of cloud infrastructure. In this role, you will be the first point of contact for platform engineers and AI architects looking to solve…
Added 2 days ago
VL
Sales Development Rep -NYC
vCluster Labs
Remote, United States
- $100,000 to $120,000 USD / year
…you are the frontline scout for the next generation of cloud infrastructure. In this role, you will be the first point of contact for platform engineers and AI architects looking to solve…
Added 2 days ago
BV
AI Platform Engineer
Bright Vision Technologies
Remote, United States
- $100,000 to $180,000 USD / year
Bright Vision Technologies is seeking a highly experienced AI Platform Engineer with 10+ years of experience in distributed systems, cloud-native infrastructure, and AI platform engineering…
Added 3 days ago
TL
Solution Architect Product Engineer/AI
The LaunchCode Foundation
Remote, United States
- $195,000 to $210,000 USD / year
Champion best practices for performance, scalability, reliability, observability, and MLOps/LLMOps across all AI delivery engagements.
Added 6 days ago
AI Engineer- Remote
Sharecare Operating Company, Inc.
Remote, United States
As the AI Engineer, you will play a critical role across vision, strategy, operations, and execution for defining and driving the transformation of Sharecare into the era of agentic…
Added 6 days ago
Solution Engineer, Data & AI
Arctiq
Remote, United States
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…
Added 10 days ago
O&
Sr. Data Solution Architect
Owens & Minor Medical Inc.
Remote, United States
- $155,000 to $160,000 USD / year
…business leaders, data engineers, application teams, security, infrastructure, and analytics stakeholders to define and implement modern data platforms, AI capabilities, and integration…
Added 10 days ago
Principal Data Engineer
Johnson & Johnson Services Inc. Legal Entity
Remote, United States
The Principal Data Engineer- AI owns product engineering and architectural decisions, serving as both the technical visionary and hands-on leader responsible for solution delivery. This…
Added 10 days ago
Senior Data Engineer - USA
Coderio
Remote, United States
DevOps, Infrastructure & Tools: Docker, Terraform, CI/CD pipelines, UNIX/Linux environments, MLOps best practices
Added 12 days ago
Senior DevOps Engineer
ECS FEDERAL LLC
Remote, United States
The Senior DevOps Engineer is responsible for accelerating the path from development to operations. The successful candidate will work in close collaboration with developers, testers,…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 12 days ago
Data & AI Engineer
RevStar
Remote, United States
Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and…
Added 13 days ago
Applied AI Engineer
Mission Underwriting Services
Remote, United States
Experience with Git, GitLab/GitHub, CI/CD pipelines, Infrastructure as Code, and DevOps/MLOps practices for deploying AI applications.
Added 16 days ago
AI/ML Lead
ISACA
Remote, United States
The AI/ML Lead is a senior, hands-on engineer and the first member of ISACA's AI implementation team, a new internal capability that will take on AI engineering work currently delivered by…

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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