Technical Content Writer
Job Location:
Monthly Salary:
Experience Required:
Posted on:
Vacancies:
Job Summary
Key Responsibilities
Develop persona-driven high-impact content across various formats including:
Technical blogs white papers solution briefs and articles
Use-case explainers tutorials case studies and how-to guides
SEO-optimized website and landing page content
Marketing assets such as email campaigns ad copy and sales funnel content
Internal and external training material
Video scripts (short-form and long-form) newsletters and product overviews
Write on advanced technology topics such as:
Generative AI Agentic AI RAG pipelines LLMs GPTs
Data Engineering tools Kafka Apache SparkSnowflake
Cloud platforms MLOps pipelines and AI agent development
Collaborate with SMEs engineers and design teams to create accurate impactful and human-centered content.
Ensure tone clarity and consistency across all deliverables while meeting SEO and readability standards.
Edit and refine content using tools for SEO originality and AI detection.
Support cross-functional teams including product marketing sales enablement and training.
Requirements
Required Skills & Qualifications
34 years of experience as a Technical Content Writer preferably in IT consulting SaaS or enterprise training domains.
Bachelors degree in Computer Science Information Technology or a related field.
Strong understanding of AI/ML concepts data platforms and cloud technologies.
Excellent writing research and editorial skills with the ability to simplify complex ideas.
Proficiency in SEO best practices keyword research and the use of AI detection/piracy tools.
Familiarity with LLM chatbots generative AI platforms and prompt engineering is a strong plus.
Self-motivated detail-oriented and capable of managing multiple content pieces simultaneously.
Benefits
Work on the front lines of AI cloud and data innovation
Collaborate with global thought leaders and enterprise clients
Be part of a growing content team with creative freedom and real impact
Competitive compensation and a learning-focused work environment
Required Skills:
Educational Background: Bachelors and Masters degrees in Data Science Computer Science Statistics or a related field. Technical Skills: Proficient in Python and familiar with key data science libraries (Pandas Scikit-Learn TensorFlow or PyTorch). Strong understanding of all complex machine learning algorithms not limited to decision trees random forests and gradient boosting machines. Competence in data preprocessing cleaning and analysis. Familiarity with data cleaning transformation and preprocessing techniques. Experience with SQL and possibly some NoSQL databases for data querying and manipulation. Basic knowledge of data visualization tools like Matplotlib and Seaborn. Strong skills in SQL for data extraction and the ability to work with complex database systems. Advanced knowledge of analytical tools and software such as Excel Tableau or more specialized software depending on the industry (e.g. SAS SPSS). Experience with data visualization and the ability to create interactive dashboards. Vast knowledge of NLP Deep Learning Machine Learning Knowledge of genAI with implementation knowledge (LLM fine tuning RAG implementation) and many more. Familiarity with cloud services (AWS Azure Google Cloud) for data processing and storage.. Professional Experience: 2-3 years of experience in a data science or related role. Proven track record of developing and deploying machine learning models to solve business problems. Experience in projects that involve complex data structures and large-scale datasets. Exposure to model validation and implementation in a production environment. Demonstrated experience in analyzing large datasets and delivering actionable insights. Proven track record of effectively communicating findings to help inform business decisions. Experience in performing statistical analysis forecasting and establishing data structures that optimize analytical capabilities. Soft Skills: Strong problem-solving skills with a capability to work through complex issues using a logical and analytical approach. Good communication skills to effectively articulate insights and technical details to non-technical stakeholders. Ability to work collaboratively in team settings and manage project timelines effectively. Strong attention to detail with the capability to work on multiple projects simultaneously. Effective communication skills capable of presenting complex information in an understandable and compelling manner. Collaboration skills to work effectively with both technical teams and business units.
