Your Role and Responsibilities
The Hybrid Integration SAAS team is looking for a Software Developer who loves working with high performing teams, wants to work with cutting edge Node.js / React and Golang technology, and thrives on helping customers become successful with AI projects.
In this role you will have an opportunity to make a big impact by helping build a global development team that excels in delighting our customers.
Key Responsibilities:

Solution Design:Lead the design of end-to-end AI solutions that encompass data acquisition, preprocessing, model selection, training, deployment, and maintenance.

Algorithm Development:Design, implement, and optimize machine learning algorithms and models that solve specific business problems, such as natural language processing, computer vision, recommendation systems, predictive analytics, etc.

Data Preprocessing:Clean, preprocess, and curate large datasets to ensure high-quality data for training and validation of AI models.

Model Training and Evaluation:Train and fine-tune AI models using appropriate techniques and frameworks. Evaluate model performance using relevant metrics and iterate on models to improve their accuracy and efficiency.

Architecture Design:Create high-level architecture designs for AI systems that consider scalability, performance, security, and integration with existing systems.

Technical Leadership:Provide guidance and mentorship to AI developers, data scientists, and engineers, ensuring adherence to best practices and architectural guidelines.

Technology Evaluation:Stay updated with emerging AI technologies, tools, and frameworks, and evaluate their suitability for solving specific business challenges.

Collaboration:Work closely with cross-functional teams, including data engineers, software developers, product managers, and domain experts, to align AI solutions with overall product development.

Proof of Concept:Develop prototypes and proof-of-concepts to demonstrate the feasibility of proposed AI solutions and gain buy-in from stakeholders.

Innovation:Explore innovative AI applications and propose ideas that can lead to new products, features, or enhancements.

Code Development:Write clean, efficient, and well-documented code using programming languages such as Python, and utilize libraries and frameworks like TensorFlow, PyTorch, scikit-learn, etc.

Ethical and Regulatory Compliance:Ensure that AI solutions meet ethical standards and regulatory requirements, particularly in areas such as data privacy, bias mitigation, and transparency.

Performance Optimization:Optimize AI models and system performance, including latency, throughput, and resource utilization, to meet business needs.

Documentation:Maintain clear documentation of the AI models, algorithms, development processes, and deployment procedures.

To be successful, you will need:

Passion for handling technical challenges and be goal and results oriented

Excellent communication skills and ability to work with multiple team

Proven listening, detail-oriented thinking, and creative problem-solving skills

Ability to work in highly collaborative global organization

Be open to flexible schedule in development and support environment

Agile development experience

What we look for:

Hands on experience in AI , Python, Java , Scala and utilize libraries and frameworks like TensorFlow, PyTorch, strongly preferred.

BE/B Tech in Computer Science or relevant and 17 to 20+ years track record in Architecture and development in a customer facing role working with enterprise software
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Required Technical and Professional Expertise

7-8 years of experience in developing enterprise applications using Java, Python, Scala, spark and related technologies with 2+ years a focus on Data Engineering, DataOps, MLOps

Knowledge of data best practices and ML/Dev operations in SaaS and hybrid environments

Software development strategies for low latency, high throughput software's

Hands-on experience with common distributed processing tools and languages Python, Spark, Hive, Presto

Deep understanding of data pipelines, data modelling strategies, schema management

Experience with specialized data architectures like data lake, data mesh and optimizing data layouts for efficient processing.

Hands on Experience with streaming platforms and frameworks like Kafka, spark-streaming

Strong understanding of advanced algorithms used in design and development of enterprise grade software

Strong understanding of data governance, data security, and data privacy best practices.

Strong expertise in working with distributed big data technologies and frameworks like Spark, Flink or Kafka.

Ability in managing and communicating data pipeline plans to internal clients

Familiarity with pipeline orchestrator tools like Argo, Kubeflow, Airflow or other open source

Familiarity with platforms like Kubernetes and experience building on top of the native platforms

Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders

Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud).

Ability to provide guidance to less experienced team members.

Preferred Technical and Professional Expertise

Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Experience working with both batch and streaming data processing pipelines using workflow engines (Argo, Tekton, etc.)

Experience developing or leveraging automated platforms for data observability, data quality and drift and systems to automatically identify and correct data issues.

Key Skills

Skills highlighted with ‘‘ are preferred keyskills