Business Development Executive

Hiring - Agent Force

Remote

Job Description

Externally facing Chat, Multilingual, Knowledge Base, Prompt Templates, Grounding

Experience Cloud -> CSS, LWC, Apex, JavaScript, Chat on the Experience Cloud Site (bots, Agent force)

Data Cloud -> As it relates to Agent Force, Search Retrievers, Data Library

Specific Use Cases:

Has worked on an Externally Facing MIAW Chat Bot that uses Agent Force AI to chat with the users.

Has used the Prompt Templates, Answer Questions with Knowledge, Flex Template

Has made external API calls from Agent Force Agent using Flow / Apex.

Overview

adesso India specialises in optimization of core business processes for organizations. Our focus is on providing state-of-the-art solutions that streamline operations and elevate productivity to new heights.

Comprised of a team of industry experts and experienced technology professionals, we ensure that our software development and implementations are reliable, robust, and seamlessly integrated with the latest technologies. By leveraging our extensive knowledge and skills, we empower businesses to achieve their objectives efficiently and effectively.

Job Description

The client’s department DPS, Digital People Solutions, offers a sophisticated portfolio of IT applications, providing a strong foundation for professional and efficient People & Organization (P&O) and Business Management, both globally and locally, for a well-known German company listed on the DAX-40 index, which includes the 40 largest and most liquid companies on the Frankfurt Stock Exchange

We are seeking talented DevOps-Engineers with focus on Elastic Stack (ELK) to join our dynamic DPS team. In this role, you will be responsible for refining and advising on the further development of an existing monitoring solution based on the Elastic Stack (ELK). You will independently handle tasks related to architecture, setup, technical migration, and documentation.

The current application landscape features multiple Java web services running on JEE application servers, primarily hosted on AWS, and integrated with various systems such as SAP, other services, and external partners. DPS is committed to delivering the best digital work experience for the customers employees and customers alike.

Responsibilities:

Install, set up, and automate rollouts using Ansible/CloudFormation for all stages (Dev, QA, Prod) in the AWS Cloud for components such as Elastic Search, Kibana, Metric beats, APM server, APM agents, and interface configuration.

Create and develop regular "Default Dashboards" for visualizing metrics from various sources like Apache Webserver, application servers and databases.

Improve and fix bugs in installation and automation routines.

Monitor CPU usage, security findings, and AWS alerts.

Develop and extend "Default Alerting" for issues like OOM errors, datasource issues, and LDAP errors.

Monitor storage space and create concepts for expanding the Elastic landscape in AWS Cloud and Elastic Cloud Enterprise (ECE).

Implement machine learning, uptime monitoring including SLA, JIRA integration, security analysis, anomaly detection, and other useful ELK Stack features.

Integrate data from AWS CloudWatch.

Document all relevant information and train involved personnel in the used technologies.

Requirements:

Experience with Elastic Stack (ELK) components and related technologies.

Proficiency in automation tools like Ansible and CloudFormation.

Strong knowledge of AWS Cloud services.

Experience in creating and managing dashboards and alerts.

Familiarity with IAM roles and rights management.

Ability to document processes and train team members.

Excellent problem-solving skills and attention to detail.

Skills & Requirements

Elastic Stack (ELK), Elasticsearch, Kibana, Logstash, Beats, APM, Ansible, CloudFormation, AWS Cloud, AWS CloudWatch, IAM roles, AWS security, Automation, Monitoring, Dashboard creation, Alerting, Anomaly detection, Machine learning integration, Uptime monitoring, JIRA integration, Apache Webserver, JEE application servers, SAP integration, Database monitoring, Troubleshooting, Performance optimization, Documentation, Training, Problem-solving, Security analysis.

Role & Responsibilities

This role will be leading analytics at WarehouseNow. You will be expected to drive data driven decision making with senior management and own product metrics

• Develop an In-depth understanding of user journeys on WarehouseNow Platforms and generate data driven insights & recommendations to help product business in meticulous decision making.
• End-to-end ownership of key metrics, work with respective product owners to understand areas we need to measure and ensure the needle is moving in the right direction.
• Develop strong hypothesis, execute A/B experiments and identify area of opportunities with strong confidence level.
• Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations
• Identify and implement streamlined processes for data reporting, dashboarding and communication
• Collaborate with Product for data tracking and implementation of tools like Google analytics, Firebase, etc. 

Key Competencies

• 3+ years of experience in core business analytics/product analytics.
• Excellent SQL, Excel abilities with working knowledge of scripting (Python, R, shell etc.)

• Background in Engineering /Statistics/Operational Research
• Bonus: Prior experience in a B2C Company

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.

• We need people with Test complete + Python.
• It's well and good to have Test Complete knowledge but Python knowledge is mandatory.
• C# is good to have too.