Arise TechGlobal
Website:
arisetg.com
Job details:
Senior Forward Deployed Engineer – AI & Data Science
Company: Arise Tech Global
Experience: 8–14 years, depending on educational qualification
Location: Hyderabad, India
Employment Type: Full-time
About Arise Tech Global
Arise Tech Global is a technology and talent solutions company helping organizations build high-performing teams across enterprise technology, infrastructure, cloud, cybersecurity, and digital transformation.
About the Role
We are looking for a Senior Forward Deployed Engineer to join an innovative AI and Data Science engineering team. This role focuses on the end-to-end technical delivery of complex AI and automation solutions, from business discovery and solution design to development, evaluation, production deployment, and stabilization.
The ideal candidate will combine hands-on engineering expertise with technical leadership, working across Applied AI/ML, Generative AI, RAG, AI agents, enterprise integrations, and MLOps/LLMOps. The role requires the ability to translate complex business problems into scalable, secure, production-ready solutions while coordinating multidisciplinary teams and delivering measurable business value.
Key Responsibilities
- Lead technical discovery by understanding business workflows, user needs, success criteria, data readiness, integration dependencies, and production constraints.
- Translate business challenges into executable solution designs, delivery plans, technical workstreams, estimates, milestones, and acceptance criteria.
- Build, prototype, review, and contribute to critical production components, including AI-enabled applications, RAG systems, bounded agents, intelligent automation, APIs, and integrations.
- Define end-to-end architecture across applications, workflows, data pipelines, models, retrieval systems, agents, enterprise integrations, identity, access controls, and observability.
- Coordinate delivery across engineering, data science, ML, testing, platform, security, compliance, and business teams.
- Establish integrated testing, AI evaluation, and governance processes covering functionality, performance, security, model quality, retrieval, generation, tool usage, and human oversight.
- Coordinate production readiness through CI/CD, staged releases, monitoring, logging, service-level objectives, rollback mechanisms, recovery procedures, and runbooks.
- Support production issue triage, early stabilization, and transition to operational teams.
- Communicate technical evidence, risks, trade-offs, and delivery progress to stakeholders.
- Measure solution adoption and business value, translating delivery insights into reusable components, accelerators, standards, documentation, and playbooks.
Required Skills & Qualifications
Education & Experience
Candidates must meet one of the following qualification and experience criteria:
- Doctorate in Computer Science, Information Technology, or a related field, with 1+ year of relevant experience.
- Master’s degree in Computer Science, Information Technology, or a related field, with 8–10 years of experience.
- Bachelor’s degree in Computer Science, Information Technology, or a related field, with 10–12 years of experience.
- Diploma in a related field, with 12–14 years of experience.
Technical Skills
- Demonstrated end-to-end technical ownership of at least one production AI, ML, software, data, or automation solution that delivered measurable enterprise outcomes.
- Strong hands-on proficiency in Python and SQL.
- Experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines, and enterprise integrations.
- Ability to translate complex business problems into technical designs, executable delivery plans, acceptance criteria, and production-readiness evidence.
- Advanced expertise in at least one of the following areas, with credible breadth across the production lifecycle:
- Applied AI/ML
- Generative AI, RAG, and AI agents
- Full-stack and integration engineering
- AI platforms and MLOps
- Strong understanding of enterprise solution architecture, cloud-native engineering, DevSecOps, and production operations.
- Familiarity with model evaluation, Responsible AI, privacy, governance, auditability, and regulated delivery requirements.
Preferred Skills
- Advanced RAG, hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integrations, and multi-agent workflows.
- Experience with AWS, Amazon Bedrock, SageMaker, Databricks, Spark, Kubernetes, serverless architectures, and event-driven systems.
- Familiarity with infrastructure as code, MLflow, Airflow, Kubeflow, observability, and FinOps.
- Experience with JavaScript/TypeScript, modern web applications, API gateways, distributed workflows, process automation, and human-AI review interfaces.
- Experience in life sciences, biotechnology, pharmaceuticals, healthcare, GxP, or validated systems.
- Experience building reusable frameworks, accelerators, engineering standards, and platform capabilities.
- Mentoring and technical capability-building experience.
Key Competencies
- Strong critical thinking and the ability to bring clarity and structure to ambiguous situations.
- Technical leadership through influence, credibility, constructive challenge, and hands-on problem-solving.
- Excellent communication skills, including the ability to explain evidence, uncertainty, risks, trade-offs, and technical limitations to diverse stakeholders.
- Strong ownership, sound judgment, and resilience when balancing business value, delivery speed, quality, security, compliance, cost, and maintainability.
- Ability to collaborate effectively with multidisciplinary and global teams.
How to Apply
Interested candidates can apply with their updated resume.
Click on Apply to know more.
