Senior Technical Lead Senior Solutions Architect (AIML)

fully flexible
Work set-up: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

10+ years in software engineering or architecture., 5+ years leading cross-functional teams in AI/ML or distributed systems., Experience designing and managing large-scale backend architectures., Proven expertise in AI/ML model deployment and performance tuning..

Key responsibilities:

  • Lead large-scale AI/ML projects ensuring alignment with business goals.
  • Architect scalable, low-latency backend systems for AI/ML workloads.
  • Oversee deployment and maintenance of AI/ML models in production environments.
  • Guide architectural decisions and mentor engineering teams.

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Proximity Works Scaleup https://www.proximity.tech/
51 - 200 Employees
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Job description

We are looking for a Senior Technical Lead Senior Solutions Architect to design, develop, and scale innovative AIMLdriven solutions. You will be responsible for architecting highly scalable, lowlatency distributed systems optimized for AIML workloads. As a key technical leader, you will solve complex challenges, influence nextgeneration AIML infrastructures, and guide crossfunctional teams to deliver stateoftheart solutions for fastgrowing startups and enterprise companies.

Be at the forefront of shaping nextgeneration AIML infrastructures, driving solutions for highimpact products across diverse industries. You’ll have the opportunity to influence key architectural decisions and enable realworld applications that scale globally, ensuring innovation and efficiency at every step.

Requirements

You’ll be responsible for —

  • Lead the execution of largescale AIML projects, ensuring alignment with business objectives.
  • Architect and design scalable, lowlatency backend architectures, focusing on AIML model serving, realtime data processing, and integration with cloud infrastructure.
  • Oversee deployment of AIML models and infrastructure, ensuring highperformance, reliability, and scalability in production environments.
  • Drive decisions for cloud platforms (AWS, GCP, or Azure), autoscaling, serverless architectures, and resource optimization.
  • Influence and guide the architectural direction of the organization, ensuring futureproof, AIMLready systems and solutions.
  • Define benchmarks and optimize performance across AIML workloads.
  • Lead technical troubleshooting, performance tuning, and architecture optimizations to ensure scalable and efficient deployment of AIML systems.
  • Mentor and provide technical guidance to engineers across multiple teams, fostering a collaborative and innovative engineering culture.
  • Communicate project progress, risks, and technical decisions effectively to stakeholders, ensuring transparency and alignment with business goals.
  • Ensure engineering best practices are followed, including CICD, TDD, version control, and test automation.
    • You need —

      • 10+ years in software engineering or architecture, including 5+ years leading crossfunctional teams in AIML or distributed systems projects.
      • Proven experience designing and managing largescale backend architectures and distributed environments, with expertise in microservices, eventdriven systems, and RESTfulGraphQL API development for AIML systems in production.
      • Extensive experience with AIML model deployment, performance tuning, model serving, and seamless integration with backend systems.
      • Deep understanding of cloud platforms (AWS, GCP, Azure), autoscaling, serverless, and faulttolerant architectures.
      • Strong experience in machine learning frameworks (TensorFlow, PyTorch) and data pipelines for realtime processing and highconcurrency environments.
      • Ability to troubleshoot and resolve complex technical challenges related to AIML workloads, scalability, and performance.
      • Excellent leadership and communication skills, with a proven ability to mentor engineers and work closely with crossfunctional stakeholders.
      • Selfstarter who excels at execution, balancing shortterm technical delivery with longterm scalability and efficiency goals.
        • Bonus points for —

          • Experience with AIML infrastructure tools like MLFlow, Kubeflow, or MLOps best practices.
          • Experience with realtime data processing & streaming technologies (Apache Kafka, Flink, Spark).
          • Familiarity with NLP frameworks (e.g., Hugging Face, spaCy)
          • Opensource contributions, side projects, or thought leadership through technical content (blogs, videos).
          • Knowledge of data privacy and security regulations relevant to AIML deployments.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Communication
  • Leadership

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