• Build internal tools and customer-facing features on top of LLMs (OpenAI, Claude, open-source models) • Design and maintain prompt chains, RAG pipelines, and agent workflows • Prototype rapidly — often going from idea to working demo in days, not sprints • Evaluate model outputs, set up evals, and iterate on quality • Wire AI into existing systems (APIs, databases, CRMs, Slack, etc.) • Own the full stack of a feature — frontend, backend, model integration, deployment

Role Description The Director of Engineering & AI-Enabled Delivery will lead a multidisciplinary, remote organization of ~150 professionals across software engineering, business analysis, design, content, and internal platforms. This leader will stabilize delivery, modernize engineering practices on cloud platforms, and build an AI-ready organization where teams use advanced tools responsibly and effectively to ship scalable products and services. Key Responsibilities - Organization and leadership: - Own the India-based engineering and delivery organization across SaaS products, custom development, and internal tools. - Design and implement a clear team structure (managers, tech leads, product/BA leads) with defined charters and accountability. - Build and develop high-performing managers and technical leaders; establish succession plans for key roles. - Engineering and AI-enabled delivery: - Define and enforce a standardized SDLC and delivery model for all teams, including cross-functional ceremonies and quality gates. - Establish cloud-native standards, reference architectures, and CI/CD pipelines for SaaS, web products, and internal tools. - Integrate AI tools into the development lifecycle (coding copilots, test generation, documentation assistants) with clear guardrails and human accountability. - Quality, reliability, and operations: - Set engineering standards for code quality, test automation, observability, and incident management. - Oversee architecture and design reviews for major initiatives; challenge and coach teams on scalability, security, and maintainability. - Own reliability metrics and continuous-improvement programs to reduce defects and incidents. - Talent development and culture: - Create and maintain a comprehensive skill matrix covering technical, AI, cloud, and cross-functional skills across all roles. - Define career paths and promotion criteria for engineers, managers, and cross-functional roles; make progression transparent and merit-based. - Build a culture of technical excellence, accountability, and continuous learning, including mentoring programs and internal knowledge sharing. - Stakeholder and strategic alignment: - Translate business goals into engineering roadmaps and capacity plans for SaaS products, client projects, and internal platforms. - Partner with US-based leadership, product, and business stakeholders to prioritize initiatives and communicate outcomes clearly. - Act as a visible champion for AI-enabled practices, helping non-technical leaders understand capabilities, risks, and ROI. Qualifications - 14-20 years in software engineering or platform engineering, including at least 5-7 years leading multi-team organizations. - Proven track record running engineering for SaaS or product organizations plus custom implementation or services work. - Strong hands-on background in modern architectures and cloud platforms (AWS, Azure, or GCP), including CI/CD and observability. - Demonstrated experience integrating AI tools into software delivery and coaching teams on responsible, effective usage. - Experience working with cross-functional teams (design, content, BAs) and aligning them around product outcomes. - Confident communicator with global stakeholders; comfortable challenging existing practices and leading change.

Role Description EPAM AI consulting practice focuses on unlocking business value for organizations through end-to-end AI/ML solutions and platforms. We are looking for an AI leader to spearhead the initiatives across our Life Sciences and Healthcare Portfolio. This is a role where you will oversee the entire lifecycle of AI solutions, from ideation through delivery and growth, in step with technology and market trends. The ideal candidate thrives in ambiguity and can continually adapt to ensure their contributions make a tangible impact in the world. - Work with EPAM's clients and EPAM internal teams (business SME's, account management teams, etc.) to shape the AI/ML/Agentic business and technology vision and GTM offerings aligned with current and emerging needs. - Manage end-to-end Data Science, AI, and Agentic projects/programs. - Lead multidisciplinary workshops and design sessions with customers. - Develop high-quality proposals in conjunction with other SMEs and consultants. - Work on EPAM's Data Science, AI, and Agentic offerings from a point of view. - Take an active part in growing the EPAM team's capacity and capability including building new competencies, selecting, and mentoring new team members. - Acts as an agent of change internally and a champion of transformation with external stakeholders. Qualifications - 10+ years of experience as Data Science Lead, Machine Learning Engineering Lead, or similar roles in the Healthcare, Pharmaceutical, MedTech/BioTech space. - 5+ years in a leadership role with team management responsibilities. - Demonstrated expertise in one or more areas of the life sciences or healthcare value chain (e.g., R&D, Clinical, Commercial, Manufacturing, Payer, or Provider), pharma manufacturing. - Great communication skills: ability to communicate AI and LSHC concepts compellingly to a variety of audiences with ease. - Hands-on experience, focused in at least one of the following domains: computer vision, NLP/language models, recommender systems, time series analytics. - Machine Learning Engineering/ Production delivery experience, ML/LLMOps. - Experience working with one or more major cloud providers. - Knowledge of one or more of the following technologies: Databricks, Snowflake, Agentic Orchestration (LangChain, Omnigent, Semantic Kernel, etc.). - Working knowledge of at least one programming language, ideally Python. - Understanding of Data Science engineering excellence and the modern SDLC for AI products. - Consulting experience (internal or through a professional services firm). Requirements - Currently acting as an AI leader for a healthcare or life science organization. - Referenceable work (papers, open-source contributions, conference talks) around the AI / ML space. - Current cloud certifications for at least one of: AWS, GCP, Azure, Databricks. - Experience navigating regulatory processes, ISO/IEC Standards, HIPAA, EU AI Act, GxP, etc.

Role Description We are seeking a talented and versatile Australian Voice Actor to support AI and machine learning projects by delivering high-quality voice recordings across various scripts, tones, and speaking styles. The ideal candidate has strong vocal control, excellent pronunciation, and the ability to perform naturally while following detailed project requirements. - Record voice scripts with clear pronunciation, natural delivery, and appropriate tone - Perform a variety of speaking styles, emotions, and character voices as required by the project - Follow recording guidelines, pronunciation standards, and script instructions - Deliver high-quality audio recordings free from background noise and technical issues - Review recordings for accuracy, consistency, and completeness before submission - Meet project deadlines and recording targets - Communicate any script ambiguities, technical issues, or recording challenges to the project team - Maintain professionalism and consistency across all recordings Qualifications - Native or near-native proficiency in Native Australian English - Excellent vocal clarity, articulation, and pronunciation - Ability to adapt tone, pace, emotion, and speaking style based on project needs - Strong reading comprehension and script interpretation skills - Reliable internet connection and access to a quiet recording environment - Basic computer skills and ability to use online recording platforms - Ability to work independently and follow detailed instructions Requirements - Previous experience in voice acting, voice-over, podcasting, broadcasting, or related audio work (Nice to Have) - Experience recording for AI, speech recognition, audiobook, gaming, or media projects (Nice to Have) - Familiarity with audio recording software and editing tools (Nice to Have) - Access to professional recording equipment, including a quality microphone and sound-treated recording space (Nice to Have)