Lead and deliver complex technology solutions for clients, integrating AI, cloud, and data platforms while managing multidisciplinary teams.
Locations (8)
New York, New York, United States
Atlanta, Georgia, United States
Boston, Massachusetts, United States
Charlotte, North Carolina, United States
Chicago, Illinois, United States
Grandview Heights, Ohio, United States
Show all 8 locations
Hoboken, New Jersey, United States
Philadelphia, Pennsylvania, United States
Compensation
The salary range for this job is:
New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $166,900 to $278,100
Bay Area California offices – $173,800 to $289,700
All other offices locations in the US, including Sacramento – $139,100 to $254,900
Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
Responsibilities
Partner with client stakeholders to understand business objectives, challenges, and opportunities.
Lead discovery, requirements definition, solution design, and implementation activities.
Design and deliver solutions across AI, cloud, data, digital, and platform engineering domains.
Translate business requirements into scalable architectures, delivery plans, and engineering workstreams.
Own solution delivery end-to-end, from problem definition through deployment and adoption.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Nice to have: Experience delivering AI solutions in financial services or another regulated industry
ILS-ingenjör hos Saab Dynamics som arbetar med Integrated Logistics Support för avancerade tekniska system.
Responsibilities
Analysera driftsäkerhet, tillgänglighet och underhållsbehov för tekniska system
Ta fram underhålls- och supportkoncept för nya och befintliga produkter
Tolka system- och kundkrav och omsätta dem till lösningar och specifikationer för logistikstöd
Arbeta med reservdelsförsörjning, teknisk dokumentation och utbildningslösningar
Genomföra analyser kopplade till exempelvis driftsäkerhet, underhåll, livscykelkostnader och reservdelsoptimering, såsom FMEA/FMECA, LCC, LORA och reservdelsanalyser
As an ILS engineer at Saab Dynamics, you work with Integrated Logistics Support (ILS) for advanced technical systems to ensure products are reliable, user-friendly, and maintainable throughout their lifecycle.
Locations (2)
Karlstad, Värmland, Sweden
Karlskoga, Nästästland, Sweden
Responsibilities
Analyze operational reliability, availability, and maintenance needs for technical systems
Develop maintenance and support concepts for new and existing products
Interpret system and customer requirements and translate them into solutions and specifications for logistics support
Work with spare parts supply, technical documentation, and training solutions
Conduct analyses related to operational reliability, maintenance, lifecycle costs, and spare parts optimization, such as FMEA/FMECA, LCC, LORA, and spare parts analysis
Requirements
Technical high school or university degree
Nice to have: Experience with complex technical systems
Apply AI engineering expertise to deploy, optimize, and scale models for strategic customers, leading technical journeys from POCs to production endpoints.
Responsibilities
Scope workloads, define metrics (TTFT, throughput, cost/token), build benchmarks, and lead technical POCs.
Serve as the technical lead for customer engineering teams through architecture reviews and rollout planning.
Tune engines (KV cache, speculative decoding, parallelism, quantization) to hit aggressive performance targets.
Profile and diagnose bottlenecks at the engine level to deliver production fixes.
Own end-to-end customer onboarding, deployment, autoscaling, capacity planning, and SLO monitoring.
A hands-on role joining the AMI team combining Machine Learning, statistical modeling, Generative AI, Retrieval-Augmented Generation (RAG), model evaluation, and applied AI experimentation for enterprise AI applications.
Compensation
The annual base salary range represents the low and high end of the BMC salary range for this position. Actual salaries depend on a wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training, licensure, and certifications; and other business and organizational needs.
Responsibilities
Design, develop, evaluate, and improve AI/ML solutions that address enterprise business and technical challenges.
Apply statistical rigor, reproducible experimentation, and MLOps/LLMOps practices to improve model quality, RAG effectiveness, and AI application performance.
Take ownership of defined Data Science initiatives, lead moderately complex or ambiguous modeling and evaluation tasks, collaborate with engineering teams on production readiness, and mentor less experienced Data Scientists.
Apply classification, regression, ranking, forecasting, clustering, and anomaly detection to enterprise AI and agentic use cases.
Develop and evaluate intent classification, semantic matching, agent/skill/tool ranking, and model-routing techniques using traditional ML, embeddings, and LLM-based approaches.
Requirements
Bachelor's degree in Data Science, Machine Learning, or Applied AI, Physics, Computer Science, or equivalent
A high-impact, engineering-led adoption role within the APAC AI Center of Excellence driving innovation in Enterprise and Sovereign AI by writing production-grade code, architecting systems, and upstreaming features to global open-source communities.
Responsibilities
Embed with strategic customers and partners to resolve deep-seated engineering blockers like SSO, legacy data pipelines, and network isolation.
Architect technical strategy and design of software solutions across multiple subsystems.
Establish, maintain, and monitor testing practices for large-scale AI systems.
Rapidly prototype and develop custom, secure platform integrations including RAG pipelines and AI agent architectures.
Harden POCs and MVPs into scalable production architectures.
Lead the architecture, development, deployment, and ongoing evolution of AI initiatives across a global consumer SuperApp. This is a hands-on technical leadership role focused on open-source foundation models, self-hosted infrastructure, and production AI systems.
Compensation
Compensation is accrued and payable following funding, after which it transitions to a regular salary, equity ownership, and OleX token participation in the overall OleOle group of companies.
Responsibilities
Establish overall AI architecture
Lead initiatives including AskOle
Lead real-time multilingual translation
Develop AI-powered sports history and content generation systems
Develop the sports data engine
Requirements
Nice to have: building consumer AI platforms at scale
Nice to have: multilingual and multimodal AI engineering
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