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Salary
$30k – $72k per year (Estimated)
Location
Remote (India)
Seniority
Staff · 8+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is an AI-powered job platform focused on remote and flexible work. It matches candidates with relevant roles using skills and preference-based algorithms, and also offers career coaching and job-search guidance.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Solutions Engineer based in India.

This is a senior, hands-on engineering role focused on designing and delivering scalable data and AI solutions in a complex enterprise environment.

You will translate business and architectural requirements into practical, buildable high- and low-level solution designs.

The role spans data platforms, pipelines, integration layers, AI-enabled applications, and reusable enterprise capabilities.

You will work closely with engineers, architects, product teams, cybersecurity, platform teams, and business stakeholders.

As a technical leader, you will influence delivery teams and technology partners without direct line-management responsibility.

You will champion engineering excellence, security, observability, reliability, and sustainable technology decisions.

The position also offers the opportunity to shape modern AI adoption through LLMs, RAG, AI agents, automation, and emerging technologies.

Accountabilities:

    • Design end-to-end data and AI solutions, translating architectural direction into detailed HLD and LLD specifications, data models, interfaces, transformation logic, error-handling strategies, SLAs, and observability requirements.
    • Establish and promote strong engineering standards covering software design, testing, CI/CD, code quality, documentation, monitoring, and operational readiness.
    • Design, build, and maintain scalable data pipelines, data products, integration layers, and distributed data solutions across the enterprise.
    • Integrate AI and machine learning capabilities into production-grade applications, including LLM-based solutions, retrieval-augmented generation (RAG), vector search, embeddings, AI agents, and unstructured data processing.
    • Evaluate technology options pragmatically, determining when to build, configure, adopt SaaS, or use low-code/no-code solutions while prioritizing scalability, reuse, cost effectiveness, and reduced technical debt.
    • Collaborate with architecture, cybersecurity, data governance, platform, and engineering teams to ensure solutions meet enterprise standards for security, resilience, compliance, performance, and maintainability.
    • Provide technical leadership and assurance across internal teams, engineering squads, and third-party partners, ensuring architectural alignment and sustainable ownership.
    • Define reliability, SLA, observability, supportability, and operational requirements for systems and services under your technical leadership.
    • Turn ambiguous business and technology challenges into practical solution options, prototypes, and implementation approaches, using AI tools to accelerate design and validation.
    • Mentor engineers, contribute to knowledge sharing, and help evolve engineering standards, communities, and best practices across the wider technology organization.
    • Requirements:

      • Bachelor’s degree in Computer Science, Engineering, or a related discipline.
      • 8+ years of hands-on experience designing, building, productionizing, and maintaining reliable and scalable data infrastructure and data products in complex environments.
      • Proven ability to create and communicate HLD and LLD artifacts, including architecture diagrams, data flows, component specifications, API contracts, data models, and operational runbooks.
      • Strong architectural and problem-solving skills, with the ability to translate high-level decisions into clear engineering specifications that development teams can implement independently.
      • Expert-level SQL skills and experience working with large-scale distributed data systems and across the full data lifecycle.
      • Strong software engineering expertise, including testing, CI/CD, code reviews, monitoring, alerting, documentation, and technical design reviews.
      • Professional development experience in an object-oriented programming language, with Python preferred; Scala, Java, or C# are also relevant.
      • Hands-on experience integrating AI/ML capabilities into production environments, including LLM APIs, RAG architectures, vector search, embeddings, or AI agents.
      • Strong understanding of modern engineering patterns such as event-driven architecture, microservices, pipeline orchestration, layered data architecture, and RAG.
      • Excellent collaboration, stakeholder management, communication, and technical influencing skills, with the ability to lead without direct people-management responsibility.
      • A proactive, adaptable, and continuous-learning mindset with a strong focus on engineering excellence.
      • Experience with AI/ML frameworks such as LangChain, LlamaIndex, Hugging Face, Weaviate, or similar tools is advantageous.
      • Familiarity with agentic frameworks such as CrewAI or AutoGen, as well as Spark, Hadoop, Hive, cloud platforms, infrastructure-as-code, and data governance tools such as Alation or Collibra, is desirable.
      • Benefits:

        • Full-time position based in Pune, India.
        • Hybrid office/remote working model.
        • Opportunity to work on large-scale data, AI, and digital transformation initiatives.
        • Senior technical leadership role with significant influence across engineering and architecture teams.
        • Exposure to modern technologies including LLMs, RAG, AI agents, cloud data platforms, and distributed data systems.
        • Opportunity to mentor engineers and contribute to engineering standards and communities.
        • Relocation assistance available for eligible candidates within India.
        • Up to 10% travel may be required.
        • Inclusive and diverse working environment with support for reasonable workplace and recruitment accommodations.
        • Potential role-specific benefits and employment conditions may apply, including applicable background, medical, or other pre-employment checks.
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