Ai-Enhanced Technology Jobs

786,411 open positions · Updated daily

AI-Enhanced Technology roles are at the forefront of digital transformation, fueling autonomous vehicles, personalized medicine, and real‑time analytics. Demand surges as enterprises adopt generative AI, multimodal models, and AI‑driven edge solutions to reduce latency and boost customer experience. The convergence of cloud-native infrastructure, container orchestration, and AI frameworks creates new opportunities for engineers and data scientists to build scalable, high‑performance systems that deliver measurable ROI within weeks of deployment.

Within the AI‑Enhanced Tech spectrum, you’ll find roles such as Machine Learning Engineer, Data Scientist, MLOps Engineer, AI Product Manager, Edge AI Developer, and AI Solutions Architect. Responsibilities range from designing and training transformer models in TensorFlow or PyTorch, to building reproducible pipelines with Airflow and MLflow, to deploying models into Kubernetes clusters on AWS SageMaker or Azure ML. Edge AI developers optimize inference on NVIDIA Jetson or Qualcomm AI SDKs, while AI product managers translate business goals into AI feature roadmaps and measure impact through A/B testing.

Salary transparency matters more than ever in AI‑Enhanced Tech. With compensation tied to market demand, equity, and specialized skill sets, clear salary ranges help professionals negotiate fair pay, evaluate opportunities across companies, and understand the true value of their expertise. Transparent data also drives diversity by reducing hidden pay gaps and empowers teams to benchmark against industry standards, fostering a healthier, more inclusive AI ecosystem.

Data Engineer

Company: IBM

Location: Austin, US

Posted Dec 09, 2025

This text describes a Data Engineer role at IBM Corporation with responsibilities involving data pipeline design, AI solutions for industrial clients, and cloud platform integration. It outlines required qualifications including advanced degrees, technical expertise in specific tools, and salary range.

Senior Cloud FullStack Developer - MERN

Company: IBM

Location: Giza, EG

Posted Dec 09, 2025

The text describes a role as an Application Developer at IBM, emphasizing opportunities to lead innovation, develop customized systems, and collaborate globally. It highlights career growth, technical expertise requirements, and the impact of the role on IBM and its clients.

Senior Scala Developer

Company: IBM

Location: Leicester, GB

Posted Dec 09, 2025

The text describes a Senior Scala Developer role at IBM Consulting, highlighting opportunities for career growth, technical expertise, and a supportive work environment. It emphasizes collaboration, innovation, and professional development while outlining responsibilities and required skills.

ITスペシャリスト(製造領域)

Company: IBM

Location: Tokyo, JP

Posted Dec 09, 2025

This job description highlights opportunities for career growth and innovation in IBM's global client collaborations, emphasizing technological solutions and professional development.

Brand Technical Specialist– Entry Level Sales Program 2026

Company: IBM

Location: Multiple Cities

Posted Dec 09, 2025

IBM's Brand Technical Specialist role emphasizes collaboration, technical expertise, and career growth, offering opportunities to innovate and solve complex business challenges through tailored solutions and digital transformation initiatives.

Application Architect-Azure Cloud

Company: IBM

Location: BANGALORE, IN

Posted Dec 09, 2025

This job description highlights opportunities to work in IBM's delivery centers, focusing on Azure solutions, cloud migration, and professional growth. It emphasizes mentorship, technical training, and diverse project experiences while requiring expertise in full-stack development and cloud technologies.

L3 SOC Analyst

Company: IBM

Location: Taguig City, PH

Posted Dec 09, 2025

This job description outlines a Senior Threat Response Analyst role focusing on cybersecurity incident response, digital forensics, and threat hunting. It details responsibilities such as advanced incident investigations, containment strategies, and collaboration with clients. Required qualifications include expertise in security technologies, forensic analysis, and certifications like GIAC or CISSP.

Associate Application Consultant-AWS Cloud

Company: IBM

Location: Singapore, SG

Posted Dec 09, 2025

The text promotes IBM Consulting's Associate Program, emphasizing professional growth, global client collaboration, and opportunities to work on innovative technologies. It highlights career development, technical skills training, and the importance of a growth mindset in solving complex client challenges.

Senior Managing Consultant - SAP HANA SCM SD (m/w/d)

Company: IBM

Location: Multiple Cities

Posted Dec 09, 2025

This job description highlights IBM Consulting's focus on long-term client relationships, innovation in hybrid cloud and AI, career development opportunities, and technical expertise in SAP solutions. It emphasizes collaboration with global clients and the use of proven methodologies to deliver impactful results.

Application Developer-Cloud FullStack

Company: IBM

Location: Hyderabad, IN

Posted Dec 09, 2025

The text describes a career in IBM Consulting focused on longterm client relationships, hybrid cloud and AI development, and collaboration with industry visionaries. It outlines responsibilities for cloud application development, required technical expertise in Java/Springboot/Angular, and preferred AWS experience.

Application Developer-ReactJS

Company: IBM

Location: BANGALORE, IN

Posted Dec 09, 2025

The text describes a job role at IBM Consulting involving technical expertise and client delivery. It outlines required skills like JavaScript, ReactJS, and cloud platforms, along with educational qualifications and preferred experiences such as familiarity with modern tools and integration with backend services.

【札幌】分散系サーバー基盤開発リーダー(金融領域)

Company: IBM

Location: Sapporo, JP

Posted Dec 09, 2025

This job description highlights a career in IBM Consulting focused on hybrid cloud and AI innovation, emphasizing collaboration with global clients, technical expertise in distributed systems, and opportunities for long-term growth. The role requires leadership in development projects and experience with specific technologies like Unix systems and Oracle databases.

Frequently Asked Questions

What are typical salary ranges by seniority for AI-Enhanced Technology roles?
Entry‑level ML Engineer or Data Scientist: $90k–$110k. Mid‑level: $120k–$150k. Senior/Lead: $160k–$200k. Staff/Principal: $210k–$260k. Director/VP: $250k–$350k (base + bonus + equity). These ranges reflect U.S. market averages for cloud‑native AI positions.
Which skills and certifications are most valuable in AI-Enhanced Technology?
Core skills: Python, PyTorch/TensorFlow, Kubernetes, Docker, CI/CD, Airflow, MLflow, SageMaker, Vertex AI, Azure ML, MLOps, reinforcement learning, generative models, NLP, CV, data engineering, SQL, Spark. Certifications: AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate, TensorFlow Developer Certificate, Certified Data Scientist (CDS), DeepLearning.AI TensorFlow Practitioner.
Is remote work common for AI-Enhanced Technology positions?
Yes. Many AI‑Enhanced Tech companies adopt remote‑first or hybrid models. Companies such as OpenAI, DeepMind, UiPath, NVIDIA, and Cloudflare offer fully remote roles; others provide 3‑4 days per week remote availability, while hardware‑lab positions may require occasional on‑site presence.
What career progression paths exist in AI-Enhanced Technology?
Typical trajectory: Junior Data Scientist → ML Engineer → MLOps Engineer → Lead ML Engineer → AI Solutions Architect → AI Product Manager → Director of AI → VP of AI. Each step adds responsibilities from model training to infrastructure management, product strategy, and executive leadership.
What are the current industry trends shaping AI-Enhanced Technology?
Key trends include generative AI and multimodal models, reinforcement learning for robotics, edge AI for IoT and autonomous vehicles, responsible AI and fairness regulation, AI‑Ops for continuous monitoring, AI‑as‑a‑Service platforms, and domain‑specific AI in healthcare diagnostics, finance fraud detection, and cybersecurity threat intelligence.

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