Note: The job is a remote job and is open to candidates in USA. SoftServe is a technology services company. The AI Technology Consultant leads the design and delivery of enterprise AI solutions, defining strategy and architectures while overseeing ML, GenAI, LLM, and data platform implementations. The role also guides cross-functional teams, engages executive stakeholders, establishes AI governance, and supports innovation and presales activities.
Responsibilities
- Lead discovery and design enterprise AI architectures that translate business needs into scalable solutions, owning end‑to‑end outcomes that drive measurable value while collaborating closely with business stakeholders, data scientists, and engineering teams
- Define AI strategy, roadmaps, and reference architectures to accelerate delivery and reduce technical risk, partnering with leadership, product teams, and clients to align AI initiatives with core business objectives
- Design and oversee implementation of ML pipelines, GenAI/LLM systems (RAG, agents), and data platforms, ensuring solutions improve performance, reliability, and scalability in collaboration with cross-functional delivery teams
- Architect secure, production-ready AI solutions, ensuring scalability, performance, and compliance through strong integration of data, models, and platforms
- Lead and mentor cross-functional teams, providing hands-on technical guidance, conducting architecture reviews, and enforcing best practices and engineering standards
- Engage executive and technical stakeholders to translate complex AI concepts into business value, leading workshops, discovery sessions, and supporting presales solutioning
- Establish AI governance frameworks including model lifecycle management, responsible AI, and regulatory compliance, while implementing monitoring for drift, bias, and model performance
- Drive innovation by exploring emerging AI and cloud technologies, developing prototypes, and building reusable accelerators that expand organizational AI capabilities
Skills
- Deep expertise in machine learning, deep learning, and Generative AI/LLMs (RAG, prompt engineering, orchestration), with strong knowledge of data architectures (lakehouse, pipelines) and distributed systems
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch), along with hands-on experience in cloud AI platforms (Azure AI, Vertex AI, AWS SageMaker) and MLOps/LLMOps practices (CI/CD, monitoring, governance)
- Strong solution architecture capabilities across data, model, application, and integration layers, with a proven track record of delivering scalable, production-grade AI systems
- Solid understanding of APIs, microservices, and big data platforms, enabling seamless integration of AI into enterprise ecosystems
- Ability to connect AI solutions to business value, translating technical capabilities into ROI-driven outcomes and measurable impact
- Experience leading client workshops, discovery sessions, and roadmap development, with strong executive communication and storytelling skills
- Familiarity with regulated environments (e.g., healthcare, finance), including compliance standards such as HIPAA and GDPR, and responsible AI practices
- Healthcare domain knowledge, including interoperability standards (FHIR, HL7, EDI), core systems (EHR/EMR, RCM), and applying AI to use cases like clinical decision support, claims automation, and patient engagement
Benefits
- If the role is eligible for a variable pay plan, this would be considered separately and may provide additional earnings beyond the base salary range reflected here.
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