Vacancies at SoluGrowth Pty Ltd

Key Responsibilities

• Develop and optimize AI/ML models with LLMs, RAG, vector databases, and modern ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Implement MLOps practices, including CI/CD for ML, model deployment, monitoring, and retraining workflows.
• Design and integrate systems using REST, GraphQL, and gRPC APIs, as well as microservices architecture.
• Utilize Docker, Kubernetes, and orchestration tools for containerization and scaling AI workloads.
• Build and maintain ETL/ELT pipelines to process structured and unstructured data across SQL/NoSQL databases.
• Deploy and manage AI workloads on cloud platforms (AWS, Azure, or GCP).
• Ensure compliance with security and regulatory standards (OAuth, JWT, data encryption, GDPR, HIPAA).
• Write clean, efficient code in Python, with additional integrations in Java, Go, or Node.js.
• Leverage Terraform, Ansible, and automation scripts for cloud infrastructure and deployment automation.
• Collaborate with cross-functional teams to ensure seamless integration of AI solutions into business applications.

Requirements

• Strong experience with AI/ML engineering, particularly LLMs, RAG, and vector databases.
• Hands-on expertise in PyTorch, TensorFlow, Hugging Face, and other ML frameworks.
• Knowledge of MLOps workflows, CI/CD for ML, and monitoring/retraining models in production.
• Proven background in system integration with APIs, microservices, Docker, and Kubernetes.
• Data engineering skills, including SQL/NoSQL, ETL/ELT, and handling large datasets.
• Proficiency in at least one cloud platform (AWS, Azure, or GCP).
• Understanding of security and compliance requirements, including OAuth, JWT, GDPR, HIPAA.
• Strong programming skills in Python; working knowledge of Java, Go, or Node.js.
• Familiarity with Terraform, Ansible, and DevOps tools for automation.
• Excellent problem-solving, communication, and collaboration skills.

Qualifications

• Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred).
• Relevant certifications in AI/ML, cloud platforms, or DevOps are advantageous.

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Key Responsibilities

• Design, build, and deploy AI/ML models across NLP, Generative AI, LLMs, Conversational AI, Agentic AI Systems, Audio Processing, and Computer Vision.
• Implement advanced AI solutions leveraging frameworks such as LangChain, RAG, PyTorch, TensorFlow, Hugging Face, and Scikit-learn.
• Work with Python, R, SQL, and distributed frameworks like PySpark to process, analyze, and model large datasets.
• Integrate AI models into production systems using APIs and application frameworks (e.g., Flask, FastAPI, Streamlit).
• Collaborate with data scientists, engineers, and product teams to deliver end-to-end AI solutions.
• Optimize model performance, ensuring scalability, efficiency, and reliability in deployment.
• Apply version control practices (GitHub, GitLab, Bitbucket) and Agile tools (e.g., JIRA).
• Leverage cloud platforms (AWS, Azure, GCP) for AI model training, deployment, and monitoring.
• Develop clear visualizations and insights using tools such as Matplotlib, Seaborn, and Plotly.

Requirements

• 2–3 years of proven experience in AI/ML engineering.
• Strong background in NLP, LLMs, Conversational AI, Generative AI, Agentic AI Systems, Computer Vision, and Audio Processing.
• Hands-on expertise with AI frameworks and tools: LangChain, RAG, PyTorch, AutoGen, TensorFlow, Keras, Hugging Face, OpenAI APIs, Scikit-learn, FastAI.
• Strong programming skills in Python (must-have), with additional experience in R, SQL, NumPy, Pandas, SciPy, PySpark.
• Experience with cloud platforms (AWS, Azure, GCP) for AI/ML workloads.
• Familiarity with visualization libraries and tools for insights (Matplotlib, Seaborn, Plotly).
• Practical knowledge of version control (GitHub, GitLab, Bitbucket) and Agile project management (JIRA).
• Experience deploying AI solutions into production using Flask, FastAPI, Elasticsearch, Streamlit, or similar tools.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or related field (Master’s preferred).
• Relevant certifications in AI/ML, cloud technologies, or data science are advantageous.

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Key Responsibilities

• Lead and manage the successful delivery of complex enterprise software, SaaS, or integration-driven projects.
• Act as the primary client-facing contact, engaging with senior business and technology stakeholders.
• Translate business needs into technical requirements and ensure alignment throughout the delivery lifecycle.
• Oversee Agile delivery models, DevOps/CI-CD practices, and governance within SDLC frameworks.
• Coordinate cross-functional teams, vendors, and stakeholders to ensure smooth delivery and value realization.
• Provide thought leadership on low-code, workflow automation, iPaaS, ETL/Reverse ETL, and AI/LLM-driven solutions.
• Ensure compliance with regional data residency and regulatory requirements, particularly within GCC/UAE markets.
• Drive continuous improvement, identifying and implementing best practices in enterprise engagement and delivery.

Requirements

• 5–7 years of proven experience in delivering enterprise software or digital transformation projects (MUST HAVE).
• Strong background in enterprise-scale implementations, SaaS platforms, and integration-heavy projects.
• Familiarity with low-code platforms, iPaaS/workflow automation, ETL/Reverse ETL, and AI/LLM-driven solutions.
• Strong knowledge of Agile delivery frameworks, DevOps/CI-CD methodologies, and SDLC governance.
• Exceptional client-facing and stakeholder management skills, with experience engaging senior executives.
• Prior exposure to Banking, Telecom, or large enterprise verticals (highly preferred).
• GCC/UAE experience, including knowledge of compliance and data residency regulations (advantageous).
• Excellent communication, problem-solving, and leadership abilities.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field (Master’s degree preferred).
• Relevant certifications (e.g., PMP, Agile, Scrum Master, SAFe, ITIL) are advantageous.