Senior Forward Deployed Engineer – AI & Data Science

Arise TechGlobal; Hyderabad; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

Arise Tech Global is seeking a Senior Forward Deployed Engineer in Hyderabad to drive end-to-end AI/automation delivery—from discovery and design to production deployment and stabilization.

Lead multidisciplinary teams across Applied AI/ML, Generative AI, RAG, AI agents, and MLOps. Translate complex business problems into scalable, secure, production-ready solutions and measurable business value.

Qualifications

• Experience delivering production AI/ML or automation solutions with measurable business outcomes.
• Strong ability to translate business problems into technical designs and delivery plans.
• Knowledge of governance, security, and compliance in production environments.

Responsibilities

• Lead technical discovery by mapping business workflows and success criteria.
• Define end-to-end architecture across data pipelines, models, and integrations.
• Prototype and review AI-enabled components, agents, and automation workflows.
• Coordinate delivery across engineering, data science, ML, security, and business teams.
• Establish testing, evaluation, and governance for AI systems and deployments.
• Drive production readiness with CI/CD, monitoring, and runbooks.
• Communicate risks, trade-offs, and progress to stakeholders.
• Capture learnings into reusable accelerators, standards, and playbooks.

Skills

Python

SQL

End-to-end ownership

APIs & integrations

MLOps

CI/CD

Cloud-native engineering

Education

PhD in CS / IT

MS in CS / IT

Bachelors in CS / IT

Diploma in related field

Tools

AWS

Bedrock / SageMaker

Databricks

Kubernetes

Job description

Experience: 8–14 years, depending on educational qualification

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 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.
• 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.